• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.143-167
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• 2015

This paper addresses the issue how the total life cycle cost may be minimized and how the cost should be allocated to the acquirer and developer. This paper differentiates post life cycle change (PLCC) endeavors from PLCC activities, rigorously classifies PLCC endeavors according to the result of PLCC endeavors, and rigorously defines the life cycle cost of a software product. This paper reviews classical definitions of software 'maintenance' types and proposes a new typology of PLCC activities too. The proposed classification schemes are exhaustive and mutually exclusive, and provide a new paradigm to review existing literatures regarding software cost estimation, software 'maintenance,' software evolution, and software architecture from a new perspective. This paper argues that the long-term interest of the acquirer is not protected properly because warranty period is typically too short and because the main concern of warranty service is given to removing the defects detected easily. Based on the observation that defects are caused solely by errors the developer has committed for software while defects are often induced by using for hardware (so, this paper cautiously proposes not to use the term 'maintenance' at all for software), this paper argues that the cost to remove defects should not be borne by the acquirer for software.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.10-13
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• 2000

This paper proposes the virtual implementation of solar cell(VISC) for photovoltaic system. It is required to make operation condition of solar cell arrays where is the limit of time and space, The main advantage of the simulator is its ability to simulate different types and sizes of arrays considering V-I characteristics of data sheet. The VISC with buch-boost converter can be used to study the short-term and long-term performances of PV cells. The simulator is a far more cost effective and reliable replacement for field and filight testing.

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1429-1435
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• 2020

Applying an accurate parametric prediction model to identify abnormal or false pressurizer water levels (PWLs) is critical to the safe operation of marine pressurized water reactors (PWRs). Recently, deep-learning-based models have proved to be a powerful feature extractor to perform high-accuracy prediction. However, the effectiveness of models still suffers from two issues in PWL prediction: the correlations shifting over time between PWL and other feature parameters, and the example imbalance between fluctuation examples (minority) and stable examples (majority). To address these problems, we propose a cost-sensitive mechanism to facilitate the model to learn the feature representation of later examples and fluctuation examples. By weighting the standard mean square error loss with a cost-sensitive factor, we develop a Cost-Sensitive Long Short-Term Memory (CSLSTM) model to predict the PWL of PWRs. The overall performance of the CSLSTM is assessed by a variety of evaluation metrics with the experimental data collected from a marine PWR simulator. The comparisons with the Long Short-Term Memory (LSTM) model and the Support Vector Regression (SVR) model demonstrate the effectiveness of the CSLSTM.

• Journal of Wind Energy
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• v.13 no.2
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• pp.5-12
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• 2022

Operations and maintenance (O&M) in offshore wind farms accounts for a substantial portion of the life cycle cost due to harsh weather conditions and vessel dispatching. In this regard, it is crucial to expedite O&M technologies in South Korea, which is in the early stage of harnessing wind resources from the ocean. This contribution investigates an O&M planning and scheduling model for floating offshore wind farms with a literature review and use case study. We introduce the development of a long- and short-term maintenance planning framework as part of an integrated O&M platform. This contains a single vessel and fleets routing composition along with technicians and a maintenance job list based on numerical algorithms. Additionally, the routing search presents the basis of decision support for economic trade-offs regarding smooth operation corresponding to ever-changing wind farm situations. The maintenance planning simulator will ultimately contribute to support yearly and day-to-day power-related decisions in a cost-effective manner.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• Journal of the Korea Institute of Building Construction
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• v.15 no.2
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• pp.209-215
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• 2015

This study was conducted to analyze the actual utilization rate of the deposit for defect repair of apartment complexes and its influential factors. We analyzed the data on enforced defect deposit cases by using one-sample t-test, Pearson's correlation analysis, and simple linear regression analysis. The difference between the deposit amount specified and the enforcement amount actually disbursed was found to about 0.51%. The change rates for short-term costs amounted approximately to $839KRW/m^2$ and 130,000 KRW/household per year, and those for long-term costs were $647KRW/m^2$ and 123,207 KRW/household per year. The results warrant the need for further research on establishing a deposit amount based on actual statistical data.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.12
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• pp.594-602
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• 1986

This paper proposes an effective algorithm for short-term generation scheduling for the purpose of economic and secure operation of thermal power systems. Especially, in the procedure of solution by Dynamic Programming, Linear Programming is introduced to promote the possibility of optimal solution and the security of power systems, and evaluation of security function is improved by the application of seven step approximation of normal distribution. Several necessary considerations, that is, time dependent start-up and constant down cost of generating units, demand and spinning reserve constraints, minimum up and sown time constraints, the number of possible start-up of a generating unit in a d and the number of generating units which can be started up at the same time at the same bus, are also incoporated to elevate the usability and flexibility of the algorithm. Finally, the effectiveness of the proposed algorithm has been demonstrated by applying to the 6-gen. 21-bus model power system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.306-312
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• 2006

Support Vector Machine(SVM), of which the foundations have been developed by Vapnik (1995), is gaining popularity thanks to many attractive features and promising empirical performance. In this paper, we propose a new short-term load forecasting technique based on SVM. We discuss the input vector selection of SVM for load forecasting and analyze the prediction performance for various SVM parameters such as kernel function, cost coefficient C, and $\varepsilon$ (the width of 8 $\varepsilon-tube$). The computer simulation shows that the prediction performance of the proposed method is superior to that of the conventional neural networks.

• Korean Institute of Interior Design Journal
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• v.25 no.6
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• pp.79-88
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• 2016

The purpose of this study was to suggest ways to vitalize residential container architecture by identifying the building process of domestic residential container architecture and analyzing various problems appeared in the process and status of construction related to planning, design, and construction. Conclusion and suggestions of this study are as follows.; firstly, according to the current situation of domestic residential container architecture, the usage was planned mainly for accommodation. Secondly, For planning background of planning preparation stage, economic benefit for long-term residence individuality and diversity for long short term complex residence were the primary planning backgrounds. Thirdly, for floor planning of planning design stage, space planning for various purposes is necessary as creating inter-space, wide LDK space, and loft by using narrow and long container for the long-term residence. Lastly, For construction stage, ways to reduce personnel expenses are being required by reducing the term of works and simplifying the processing stage by running factory production and field construction in parallel. If reduction method of construction cost through energy saving and mass production system is considered in the future, it would be possible to expand the development to dormitory and community housing for university students who are pressured by housing cost.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.920-930
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• 2019

To figure out the impact of debt financing on the profits of industrial enterprises, it starts with calculating the first differences against the logarithms of the cost profit ratios and the debt asset ratios of Chinese industrial enterprises during 179 months from 2002 to 2016; next, it runs the cointegration test and afterwards the regression test to analyze the obtained first differences, and still next uses the Simulink software to get the regularity of those changes. It finds out that there is not only a long-term stable relationship between the enterprises' profits and debts, but also a steady time series trend within a short term. The profit rate positively correlates to the debt asset ratio, and profit for the current term positively correlates to the profit for the previous term. It indicates that properly raised debts can help increase the profit rate of the industrial enterprises, and a higher previous profit level can help improve the current profit level.