• Journal of Korean Society for Quality Management
• /
• v.47 no.1
• /
• pp.187-198
• /
• 2019

Purpose: In this study, a reliability prediction based reliability growth management is suggested especially for the early development phase of a system and the case study of surveillance system is given. Methods: The proposed reliability prediction based reliability growth management procedures consists of 7 Steps. In Step 1, the stages for reliability growth management are classified according to the major design changes. From Step 2 to Step 5, system reliability is predicted based on reliability structures and the predicted reliabilities of subsystems (Level 2) and modules (Level 3). At each stage, by comparing the predicted system reliability with that of the previous stage, the reliability growth of the system is checked in Step 6. In Step 7, when the predicted value of sustem reliability does not satisfy the reliability goal, some design alternatives are considered and suggested to improve the system reliability. Results: The proposed reliability prediction based reliability growth management can be an efficient alternative for managing reliability growth of a system in its early development phase. The case study shows that it is applicable to weapon system such as a surveillance system. Conclusion: In this study, the procedures for a reliability prediction based reliability growth management are proposed to satisfy the reliability goal of the system efficiently. And it is expected that the use of the proposed procedures would reduce, in the test and evaluation phase, the number of corrective actions and its cost as well.

• Journal of Information Processing Systems
• /
• v.11 no.1
• /
• pp.39-56
• /
• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• Journal of the Korea Concrete Institute
• /
• v.11 no.6
• /
• pp.89-100
• /
• 1999

Service life of concrete structures that are exposed to the environmental attack is largely influenced by the corrosion of reinforcing bare due to the chloride contamination. Chloride ions penetrate continuously into concrete from the environment, and chloride diffusion velocity is governed by a mechanical steady stage. In this study, a method is developed to predict corrosion initiation of reinforcing bars in the sea-shore structures, based on governing equations that take into account the diffusing of chloride ions and a mechanical steady state. As a result of this study, Corrosion Prediction System (CPS) is developed, and it can be used to determine an optimal time for repair and rehabilitation actions need to be taken. Futhermore, CPS assists the concrete mixing structures by predicting of chloride concentrations in concrete mixture, exposed to salt concentrations and service environment.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.05a
• /
• pp.351-352
• /
• 2006

There are many methodologies fur doing analysis of system's reliability in early design stage. Among the methods, PRISM is, as compared to MIL-HDBK-217, a newly developed technology but not easy to use. Because PRISM provides models that predict a part failure rate and field database, called EPRD and NPRD that can be combined with prediction models. This paper presents some capabilities of the prediction models in PRISM and usability of EPRD and NPRD database in system level reliability prediction.

• Tunnel and Underground Space
• /
• v.4 no.1
• /
• pp.63-76
• /
• 1994

This paper discusses contents of the existing design, the behaviours prediction on the strut and retaining wall around subsurfaces, and also evaluates the measured results in comparison with the management criterion during excavation period of ventilation shaft at Pusan-Subway 220. Field measurements showed that maximum displacement 23.74 mm at boundary site of multistratification and the weathered rock to be formed at 0.2~0.6 H of total excavating depth(H), 68 ton of maximum axial force and 4.4X102 kg/cm2 of stress on strut. The measured axial force exceeds prediction levels by up to 50 percent at the weathered soil & rock, and the others come under the category of their levels. The great gap of both field measurements and prediction on behaviour makes a difference of the site situation at the design stage and the practical working. This measured value is greatly safety in comparison with that of the safety criterion, but axial force at 4~5 strut of ventilation shaft l is higher than the prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.12
• /
• pp.3100-3116
• /
• 2012

Reversible data hiding enables the embedding of messages in a host image without any loss of host content, which is proposed for image authentication that if the watermarked image is deemed authentic, we can revert it to the exact copy of the original image before the embedding occurred. In this paper, we present an improved histogram-based reversible data hiding scheme based on prediction and sorting. A rhombus prediction is employed to explore the prediction for histogram-based embedding. Sorting the prediction has a good influence on increasing the embedding capacity. Characteristics of the pixel difference are used to achieve large hiding capacity while keeping low distortion. The proposed scheme exploits a two-stage embedding strategy to solve the problem about communicating peak points. We also present a histogram shifting technique to prevent overflow and underflow. Performance comparisons with other existing reversible data hiding schemes are provided to demonstrate the superiority of the proposed scheme.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.497-501
• /
• 2013

An important decision-making element for the success of housing redevelopment projects is a prediction of the profitability of redevelopment. Risk factors influencing profitability were deduced through a review of the literature about profitability and a risk analysis developed by a survey of maintenance projects. In addition, a profitability prediction depending on the analysis of risk factors is necessary to judge the business feasibility of a project in the planning stages. A profitability prediction model of management and disposal method, which is calculated by proportional rate and which helps estimate contributions to profitability, is proposed to prevent difficulties in business development. The proposed model has the potential to prevent interruptions, reduce the length of projects, generate cost savings, and enable rational decision-making during the project period by allowing a judgment of profitability at the planning stage.

• Geotechnical Engineering
• /
• v.13 no.6
• /
• pp.5-12
• /
• 1997

Predictions of settlements under preloading for the improvement of soft soil is a very important element of construction management. Due to the non uniformity, difficulty of estimating resonable soil properties, predictions of settlements and settlement velocities at the design stage seldom agree with the actual future settlements. To overcome this problem, the prediction methods based on the settlement observation of initial preloading stage such as hyperbolic method and Asaoka method have been employed frequently. However the estimating method for the reliability of these predictions at the time of prediction has not been suggested. In this study, comparisons of predicted settlements by hyperbolic met hed and observed settlements are explored through case studies. And a stratagem of estimating reliability of settlement predictions by hyperbolic method is suggested as the result of investigation on the relationship between the initial observed time and error of settlement prediction by hyperbolic method.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.6
• /
• pp.1652-1659
• /
• 1998

To provide performance gains by reducing the operand referencing latency and data cache bandwidth requirements, we present an operand reference prediction cache (ORPC) which predicts operand value and address translation during the instruction fetch stage. The prediction is verified in the early stage, and thus it minimizes the performance penalty caused by the misprediction. Through the trace-driven simulation of six benchmark programs, the performance improvement by proposed three aRPC stmctures (OfiPC1, OfiPC2. ORPC3)is analysed and validated.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.3
• /
• pp.393-398
• /
• 2015

City or Community-scale Energy Management System(CEMS) is used to reduce the total energy consumed in the city by arranging the energy resources efficiently at the planning stage and controlling them economically at the operating stage. Of the operational functions of the CEMS, generation forecasting of renewable energy resources is an essential feature for the effective supply scheduling. This is because it can develop daily operating schedules of controllable generators in the city (e.g. diesel turbine, micro-gas turbine, ESS, CHP and so on) in order to minimize the inflow of the external power supply system, considering the amount of power generated by the uncontrollable renewable energy resources. This paper is written to introduce numerical models for photo-voltaic power generation prediction based on the weather forecasting information. Unlike the conventional methods using the average radiation or average utilization rate, the proposed models are developed for CEMS applications using the realtime weather forecast information provided by the National Weather Service.