• KDI Journal of Economic Policy
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• v.28 no.2
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• pp.51-96
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• 2006

Two conditions should be satisfied if fiscal policy is to stabilize economic cycles; proper policy timing and significant policy effect. This paper evaluates whether the policy timing has been proper in Korea by investigating the correlation between fiscal policy stance and economic conditions. We first calculate quarterly FIs (Fiscal Impulse) using the estimated potential GDP and fiscal balance data. Based on these indices, we 1) analyze how FIs respond to the economic conditions summarized in GDP gap through regression analysis, 2) compare average FIs in expansionary and recessionary periods according to the NSO's economic cycles, 3) evaluate fiscal policy maker's perception of economic conditions and its intention by reviewing the budget proposals. Although regression analysis shows that overall fiscal policy, especially expenditure side, has properly responded to economic conditions, average FIs do not show the significant difference between expansionary and recessionary periods. It is inconclusive whether the fiscal policy timing has been proper. Budget proposals show that actual fiscal policy stance has been sometimes inconsistent with the policy intention, which implies that it is hard to utilize fiscal policy actively to stabilize the economy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.4
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• pp.565-572
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• 2010

It is difficult to predict the accurate fatigue life of the ship structure because of load uncertainty and load redistribution at the ship structure members. As one of studies for accurate evaluation and prediction of fatigue life, it is a promising way to detect the crack previously by attaching the Fatigue Indicator Sensor (FIS) at the crack prediction region. In order to predict the fatigue life of the ship structure by using FIS, it is required to know previously the crack propagation characteristics according to pre-notch shapes. In this study, we obtained the stress distribution phase, stress concentration factors and stress intensity factor of various pre-notch shapes through FEA. Additionally, we conducted the fatigue test and obtained the characteristics of crack propagation according to the pre-notch shapes through comparison between the fatigue test and the FEA. Consequently, we classified the pre-notch shape into 3 categories: Long, Medium, and Short life type. On the basis of the numerical and experimental results, the FIS can be developed.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.1-7
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• 2021

In this paper, We focused the issue of creating a socially problematic nurse schedule. The nurse schedule should be prepared in consideration of three shifts, appropriate placement of experienced workers, the fairness of work assignment, and legal work standards. Because of the complex structure of the nurse schedule, which must reflect various requirements, in most hospitals, the nurse in charge writes it by hand with a lot of time and effort. This study attempted to automatically create an optimized nurse schedule based on legal labor standards and fairness. We developed an I/O Q-Learning algorithm-based model based on Python and Web Application for automatic nurse schedule. The model was trained to converge to 100 by creating an Fairness Indicator Score(FIS) that considers Labor Standards Act, Work equity, Work preference. Manual nurse schedules and this model are compared with FIS. This model showed a higher work equity index of 13.31 points, work preference index of 1.52 points, and FIS of 16.38 points. This study was able to automatically generate nurse schedule based on reinforcement Learning. In addition, as a result of creating the nurse schedule of E hospital using this model, it was possible to reduce the time required from 88 hours to 3 hours. If additional supplementation of FIS and reinforcement Learning techniques such as DQN, CNN, Monte Carlo Simulation and AlphaZero additionally utilize a more an optimized model can be developed.

• Structural Engineering and Mechanics
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• v.67 no.5
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• pp.457-464
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• 2018

This paper presents a method for detecting damage in irregular 2D and 3D continuum structures based on combination of wavelet transform (WT) with fuzzy inference system (FIS) and particle swarm optimization (PSO). Many damage detection methods study regular structures. This method studies irregular structures and doesn't need response of healthy structures. First the damaged structure is analyzed with finite element methods, and damage response is obtained at the finite element points that have irregular distance, secondly the FIS, which is optimized by PSO is used to obtain responses at points, having equal distance by response at those points that previously obtained by the finite element methods. Then a 2D (for 2D continuum structures) or a 3D (for 3D continuum structures) matrix is performed by equal distance point response. Thirdly, by applying 2D or 3D wavelet transform on 2D or 3D matrix that previously obtained by FIS detail matrix coefficient of WT is obtained. It is shown that detail matrix coefficient can determine the damage zone of the structure by perturbation in the damaged area. In order to illustrate the capability of proposed method some examples are considered.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.30-35
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• 1993

Simple recurrence relations for calculating completion times of various storage polices (unlimited, intermediate storages(FIS), finite intermediate storages(FIS), no intermediate storage(NIS), zero wait(ZW) for serial multi-product multi-unit processes are suggested. Not only processing times but also transfer times, set-up (clean-up) times of units and set-up times of storages are considered. Optimal scheduling strategies with zero transfer times and zero set-up times had been developed as a mixed integer linear programniing(MILP) formulation for several intermediate storage policies. In this paper those with non-zero transfer times, non-zero set-up times of units and set-up times of storages are newly proposed as a mixed integer nonlinear programming(MINLP) formulation for various storage polices (UIS, NIS, FIS, and ZW). Several examples are tested to evaluate the robustness of this strategy and reasonable computation times.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.777-780
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• 1998

물체의 3차원적인 정보를 복원하는 일은 그 정보의 일련된 이용에 있어서 중요한 문제이다. 이를 위해 여러가지 방법들이 연구되고 있으며, 그 중 shape from focus(SFF) 방법은 영상의 초점이 맞는 렌즈의 위치를 찾아내어 렌즈 공식에 의해 초점이 맞는 부분의 거리 정보를 구할 수 있다. 기존의 이 방법은 초점이 맞았는지의 정도를 계산하기 위한 focus measure 값들을 카메라의 광학축에 수직인 단순한 평면으로 가정하여 그 합이 최대가 되는 위치를 찾아내었다. 이를 개선하기 위해서 focused image surface(FIS) 개념이 연구되었고 그로 인해 더욱 나아진 결과를 얻었다. 물체의 FIS는 카메라 렌즈에 의해 초점이 맞게된 물체의 점들의 집합으로 이루어진 공간상의 면이다. 기하광학에 의해 물체의 모양과 FIS 상이에는 일대일 대응 관계가 있고 FIS의 형태를 구하는것이 결국은 물체의 모양을 복원하는것이다. FIS 개념을 처음 적용할 때는 물체의 모양이 부분적으로 영상 탐지기(image detector)와 같은 평면으로 가정하여 3차원 공간상에서 가능한 모든 방향의 평면에 대한 focus measure를 구하여 그 값이 최대가 되는 렌즈의 위치를 구하였다. 그러나 이러한 방법은 focus measure의 합이 정사각형의 윈도우에서 계산되기 때문에 곡면으로 이루어진 실제 물체에서는 오차르 ㄹ가지게 된다. 본 논문에서는 이와는 달이 평면이 아닌 곡면에 대한 focus measure의 합이 최대가 되는 렌즈의 위치를 구하여 이전의 방법들 보다 정확한 복원이 가능함을 보인다.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.105-109
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• 2012

The current status of the AKARI-FIS Point Source Catalogue is reported. The first version of the Bright Source Catalogue has been in public since March 2010 and used extensively in the various fields in astronomy. The second version of the Bright Source Catalogue and the first version of the Faint Source Catalogue are currently under development. The revised Bright Source Catalogue is expected to have improved completeness, reliability, and accuracy compared to the current version. The Faint Source Catalogue will have a scan-density dependent detection limit and will enable much deeper exploration of the sky especially in the high-ecliptic latitude regions. Both catalogues will be available in a year time scale.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.449-457
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• 2000

The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.49-53
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• 2017

The point sources in the Bright Source Catalogue of the AKARI Far-Infrared Surveyor (FIS) were classified based on their FIR and mid-IR fluxes and colours into young stellar object (YSO) and extragalactic source types using a Quadratic Discriminant Analysis method (QDA) and Support Vector Machines (SVM). The reliability of the selection of YSO candidates is high, and the number of known YSO candidates were increased significantly, that we demonstrate in the case of the nearby open cluster IC348. Our results show that we can separate galactic and extragalactic AKARI point sources in the multidimensioal space of FIR fluxes and colours with high reliability, however, differentiating among the extragalactic sub-types needs further information.