• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.11
• /
• pp.1700-1713
• /
• 2018

Objective: The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods: A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results: The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam's sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion: The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

• Water for future
• /
• v.27 no.2
• /
• pp.147-154
• /
• 1994

The occurrence condition of debris fiow due to rainfall is given by solving the equations for fiow on a slope. The solution shows that a debris fiow will occur on a slope when the accumulated rainfall within the time of concentration exceeds a certain value determined by the properties of the slope. To estimate this critical value, the system analysis technique would be commendable. In this study, a procedure to fine the critical rainfall from the rainfall data whith and without debris flows is proposed. Reliability of this method is verified by applying to the debris flows in Unzen Volcano which recently began to erupt. Discharge of debris flow in a stream is obtained by solving the equation of continuity using the kinematic wave theory and assuming the cross sectional area to be a function of discharge. The computed hydrographs agree weel with the ones observed at the rivers in Sakurajima and Unzen Volcanos. It is found from the derived equation that the runoff intensity of debris flow is in proportion to the rainfall intensity and accumulated rainfall, jointly. This gives a theoretical basis to the conventional method which has been widely used.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.12
• /
• pp.729-734
• /
• 2017

A safety relief valve is a device that relieves excessive pressure in piping lines or tanks and maintains pressure at the appropriate pressure level for use. The (pressure in the) safety valve is directly influenced by the change in the back pressure, depending on whether the vents in the spring bonnet are vented to the atmosphere or to the outlet. The back pressure is divided into the built-up back pressure and the superimposed back pressure, and the back pressure characteristics vary according to the usage conditions. The safety valve used in this study is a Conventional Safety Relief Valve. The blowdown of the safety valve is predicted by establishing the equilibrium equation between the opening force and spring force considering the back pressure characteristics. Its reliability is secured by using CFX17.1. In addition, the safety of the safety valve trim was examined through fluid-structure interaction analysis.

• Journal of Digital Convergence
• /
• v.15 no.5
• /
• pp.61-69
• /
• 2017

This study aims to investigate the public big data standard analysis model developed by Ministry of the Interior and examine its accuracy and reliability of prediction. To do this, big data standard analysis index were calculated to apply them to the real world case of CCTV monitoring system prior installation in K city. The result of this case study revealed that the areas to be installed CCTV consisted with the area where residences requested and complained to install CCTV monitoring systems, which indicated that the result of big data standard analysis model provided accurate and reliable outcomes. The result of this study suggested implications on effective exploitation of big data analysis.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.10
• /
• pp.1291-1296
• /
• 2013

Risk-based inspection (RBI) is a well-known method that is used to optimize inspection activities based on risk analysis in order to identify the high-risk components of major facilities such as power plants. RBI, when implemented and maintained properly, improves plant reliability and safety while reducing unplanned outages and repair costs. Risk is given by the product of the probability of failure (POF) and the consequence of failure (COF). A semi-quantitative method is generally used for risk assessment. Semi-quantitative risk assessment complements the low accuracy of qualitative risk assessment and the high expense and long calculation time of quantitative risk assessment. The first step of RBI is to identify important failure modes and causes in the equipment. Once these are defined, the POF and COF can be assessed for each failure. During POF and COF assessment, an effective inspection method and range can be easily found. In this paper, the calculation of the POF is improved for accurate risk assessment. A modified semi-quantitative risk assessment was carried out for boiler facilities of thermal power plants, and the next maintenance schedules for the equipment were decided.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.13 no.4
• /
• pp.253-262
• /
• 2015

Radionuclide deposited on the surface of several internal and external systems in a nuclear power plant is created by the activation of corrosion products from nuclear reactor structural materials and fission products. Especially, the constant contact between water and the surface corrodes the inside where primary system makes coolants and corrosion products mixed. Also, these are circulated along the systems. For comparing models, CRUDTRAN, DISER, MIGA-RT and CPAIR codes are analyzed to predict the quantity of radionuclide and corrosion product of primary reactor that are used at the stage of designing. The corrosion products behavior of domestic PWR primary system was predicted by using CRUDTRAN. This study aims to increase the reliability of corrosion product evaluation model by comparing the actual values and calculated values with the data of a Westing House-type Nuclear Power Plant.

• Journal of Korean Society on Water Environment
• /
• v.30 no.1
• /
• pp.16-24
• /
• 2014

A combined watershed and receiving waterbody model was developed for operational water flow forecasting of the Nakdong river. The Hydrological Simulation Program Fortran (HSPF) was used for simulating the flow rates at major tributaries. To simulate the flow dynamics in the main stream, a three-dimensional hydrodynamic model, EFDC was used with the inputs derived from the HSPF simulation. The combined models were calibrated and verified using the data measured under different hydrometeological and hydraulic conditions. The model results were generally in good agreement with the field measurements in both calibration and verification. The 7-days forecasting performance of water flows in the Nakdong river was satisfying compared with model calibration results. The forecasting results suggested that the water flow forecasting errors were primarily attributed to the uncertainties of the models, numerical weather prediction, and water release at the hydraulic structures such as upstream dams and weirs. From the results, it is concluded that the combined watershed-waterbody model could successfully simulate the water flows in the Nakdong river. Also, it is suggested that integrating real-time data and information of dam/weir operation plans into model simulation would be essential to improve forecasting reliability.

• International Journal of Automotive Technology
• /
• v.4 no.2
• /
• pp.87-94
• /
• 2003

Recent advancements of permanent magnet (PM) materials and solid-state devices have contributed to a substantial performance improvement of permanent magnet machines. Owing to the rare-earth PMs, these motors have higher efficiency, power factor, output power per mass and volume, and better dynamic performance than induction motors without sacrificing reliability. Not surprisingly, they are continuously receiving serious considerations for a variety of automotive and propulsion applications. An electric vehicle (EV) requires a high-effficient propulsion system having a wide operating range and a capability of generating a high peak torque for short durations. The improvement of torque-speed performance for these systems is consequently very important, and researches in various aspects are therefore being actively pursued. A great emphasis has been placed on the efficiency and optimal utilization of PM machines. This requires attention to many aspects related to the machine design and overall performance. In this respect, the prediction of iron losses is particularly indispensable and challenging, especially for drives with a deep field-weakening range. The objective of this paper is to present iron loss estimations of a PM motor over a wide speed range. As aforementioned, in EV applications core losses can be significant during high-speed operation and it is imperative to evaluate these losses accurately and take them into consideration during the motor design stage. In this investigation, the losses are predicted by using an analytical model and a 2D time-stepped finite element method (FEM). The results from different analytical approaches are compared with the FEM computations. The validity of each model is then evaluated by these comparisons.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.28 no.6
• /
• pp.319-331
• /
• 2016

This study explores the signal characteristics for different averaging intervals and defines representative verticies for each observatory by criterion of percent rate and variance. The shorter averaging interval shows the higher frequency variation, though the lower percent rate. In the tidal currents, we could hardly find the differences between 60-minute and 20-minute averaging. The newly defined criterion improves reliability of HF-radar data compared with the present reference which deselects the half by percent rate.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.10
• /
• pp.5115-5122
• /
• 2013

This paper has studied about the development and application of landslide collapse prediction real-time monitoring system based on USN to detect and measure the collapse of landslide. The rainfall measuring sensor, gap water pressure sensor, indicator displacement measuring sensor, index inclination sensor, water content sensor and image analysis sensor are selected and these are applied on the test bed. Each sensor's operation and performance for reliability verification is tested by the instrument which is installed in the field. As the result, u-IT based real-time landslide monitoring system which is developed by this research for landslide collapse detection could minimize life and property damages because it makes advance evacuation with collapse risk pre-estimate through real-time monitoring on roadside cut and bedrock slopes. This system is based on the results of this study demonstrate the effect escarpment plan are spread throughout.