• Water Engineering Research
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• v.3 no.1
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• pp.57-62
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• 2002

This research is intended to integrate long-term operation rules and real time operation policy for conservation & flood control in a reservoir. The familiar Yield model has been modified and used to provide long-term rule curves. The model employs linear programming technique under given physical conditions, i.e., total capacity, dead storage, spillways, outlet capacity and their respective elevations to find required and desired minimum storage fur different demands. To investigate the system behavior resulting from the above-mentioned operating policy, i.e., the rule curves, the simulation model was used. Results of the simulation model show that the results of the optimization model are indeed valid. After confirmation of the above mentioned rule curves by the simulation models, gate operation procedure was merged with the long term operation rules to determine the optimum reservoir operating policy. In the gate operation procedure, operating policy in downstream flood plain, i.e., determination of damaging and non-damaging discharges in flood plain, peak floods, which could be routed by reservoir, are determined. Also outflow hydrograph and variations of water surface levels for two known hydrographs are determined. To examine efficiency of the above-mentioned models and their ability in determining the optimum operation policy, Esteghlal reservoir in Iran was analyzed as a case study. A numerical model fur the solution of two-dimensional dam break problems using fractional step method is developed on unstructured grid. The model is based on second-order Weighted Averaged Flux(WAF) scheme with HLLC approximate Riemann solver. To control the nonphysical oscillations associated with second-order accuracy, TVD scheme with SUPERBEE limiter is used. The developed model is verified by comparing the computational solutions with analytic solutions in idealized test cases. Very good agreements have been achieved in the verifications.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.161-167
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• 2010

In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.219-225
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• 2013

Program and erase characteristics of the elliptic gate all around (e-GAA) SONOS cell have been studied as the variation of eccentricity of the channel. An analytic program and erase model for the elliptic GAA SONOS cell is proposed and evaluated. The model shows that the ISPP (incremental-step-pulse programming) property is changed non-linearly as the eccentricity of the e-GAA SONOS cell is increased. It is differently from the well known linear relationship for that of 2D SONOS and even 3D circular SONOS cell with program bias. We can find that the simulation results of ISPP characteristics are in accord with the experimental data.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.53-62
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• 2015

Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.179-190
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• 2010

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and incorporate the ability of SA to avoid being trapped in a local optimum. The APSO-SA algorithm efficiency is verified using some benchmark functions. This paper presents the application of APSO-SA to find the optimal location, type and size of flexible AC transmission system devices. Two types of FACTS devices, the thyristor controlled series capacitor (TCSC) and the static VAR compensator (SVC), are considered. The main objectives of the presented method are increasing the voltage stability index and over load factor, decreasing the cost of investment and total real power losses in the power system. In this regard, two cases are considered: single-type devices (same type of FACTS devices) and multi-type devices (combination of TCSC, SVC). Using the proposed method, the locations, type and sizes of FACTS devices are obtained to reach the optimal objective function. The APSO-SA is used to solve the above non.linear programming optimization problem for better accuracy and fast convergence and its results are compared with results of conventional PSO. The presented method expands the search space, improves performance and accelerates to the speed convergence, in comparison with the conventional PSO algorithm. The optimization results are compared with the standard PSO method. This comparison confirms the efficiency and validity of the proposed method. The proposed approach is examined and tested on IEEE 14 bus systems by MATLAB software. Numerical results demonstrate that the APSO-SA is fast and has a much lower computational cost.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.54-67
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• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.53-63
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• 1999

For the close range digital photogrammetry, multi-step procedures should be embodied in an integrated system. However, it is hard to construct an Integrated system through conventional procedural processing. Using Object Oriented Programming(OOP), photogrammetric processings can be classified with corresponding subjects and it is easy to construct an integrated system lot digital photogrammetry as well as to add the newly developed classes. In this study, the equation of 3-dimensional mathematic model is developed to make an immediate calibration of the CCD camera, the focus distance of which varies according to the distance of the object. Classes for the input and output of images are also generated to carry out the close range digital photogrammetric procedures by OOP. Image matching, coordinate transformation, dirct linear transformation and bundle adjustment are performed by producing classes corresponding to each part of data processing. The bundle adjustment, which adds the principle coordinate and focal length term to the non-photogrammetric CCD camera, is found to increase usability of the CCD camera and the accuracy of object positioning. In conclusion, classes and their hierarchies in the digital photogrammetry are designed to manage multi-step procedures using OOP and close range digital photogrammetric process is implemented using CCD camera in an integrated System.

• Management & Information Systems Review
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• v.33 no.5
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• pp.85-95
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• 2014

This paper suggested an efficient mathematical model for strategic alliance of liner shipping companies. Even though a few previous research papers proposed the mathematical models for container slot chartering and allocation under liner shipping, those models were nonlinear and very difficult to solve. So their models had limits to apply them to real world problems. On the other hand, the model suggested in this paper is easy to solve and apply to real world problems because it is a integer linear programming model. This paper tried to apply the model to the same example problem as used in existing research paper. Excel add-in program, Premium Solver Platform was used to solve the problem and the optimal allocation and slot chartering for containers were able to be found easily. The result also showed that the total container shipping cost for applying the strategic alliance model was reduced compared to non-strategic alliance model.

• Journal of the Korean Society of Costume
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• v.57 no.2 s.111
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• pp.69-85
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• 2007

Despite the recovery of consumer expenditure and retailing in the Korean economy after 2001, the domestic apparel industry has been aggravated by negative growth in both productivity and production. The purpose of the stud? is to diagnose the develop competitive of the Korean apparel industry and derive implications for this after estimating the efficiency of the Korean apparel companies with Data Envelopment Analysis. Data Envelopment Analysis(DEA) is a methodology based in non-parametric analysis and linear programming. It was developed for measuring the relative efficiency of a set of firms that use inputs to produce outputs. Data used fer input and output variables in the analysis are drawn from financial statement recorded by the Korean Financial Supervisory Service. The initial input data comprise the number fo the employees, fixed assets, general management and selling expenses, and cost of sales. The initial outputs are the operating profit and the gross margin. To summary the results, the efficiencies of the Korean apparel companies has increased yearly in spite of being overabundance of investment in Labour and Capital. According to correlation between input and output variables, the Korean apparel industry has been revamping gradually from labor intensive industries to the capital. The companies need to reduce costs in the results from the number of employees, fixed asset and cost of sales to transform into an efficiently enterprise. The companies owning or obtaining a brand had bitter establish an outsourcing strategic in production, while OEM corporations are called far setting up a manufactory in domestic or abroad. Although the paper is derived some implications with production efficiencies, the relation between apparel companies and brand power, consumption level of consumer, and social trend is remained on a limitation to the study. The next research necessitates a topic with Fashion industry or examining the correlation between brand value, social propensity and profit margin.