• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.9
• /
• pp.1177-1184
• /
• 1999

본 논문에서는 스캔플립프롭 선택 시간이 짧고 높은 고장 검출률(fault coverage)을 얻을 수 있는 새로운 부분스캔 설계 기술을 제안한다. 순차회로에서 테스트패턴 생성을 용이하게 하기 위하여 완전스캔 및 부분스캔 설계 기술이 널리 이용되고 있다. 스캔 설계로 인한 추가영역을 최소화 하고 최대의 고장 검출률을 목표로 하는 부분스캔 기술은 크게 구조분석과 테스트 가능도(testability)에 의한 설계 기술로 나누어 볼 수 있다. 구조분석에 의한 부분스캔은 짧은 시간에 스캔플립프롭을 선택할 수 있지만 고장 검출률은 낮다. 반면 테스트 가능도에 의한 부분스캔은 구조분석에 의한 부분스캔보다 스캔플립프롭의 선택 시간이 많이 걸리는 단점이 있지만 높은 고장 검출률을 나타낸다. 본 논문에서는 구조분석에 의한 부분스캔과 테스트 가능도에 의한 부분스캔 설계 기술의 장단점을 비교.분석하여 통합함으로써 스캔플립프롭 선택 시간을 단축하고 고장 검출률을 높일 수 있는 새로운 부분스캔 설계 기술을 제안한다. 실험결과 대부분의 ISCAS89 벤치마크 회로에서 스캔플립프롭 선택 시간은 현격히 감소하였고 비교적 높은 고장 검출률을 나타내었다.Abstract This paper provides a new partial scan design technique which not only reduces the time for selecting scan flip-flops but also improves fault coverage. To simplify the problem of the test pattern generation in the sequential circuits, full scan and partial scan design techniques have been widely adopted. The partial scan techniques which aim at minimizing the area overhead while maximizing the fault coverage, can be classified into the techniques based on structural analysis and testabilities. In case of the partial scan by structural analysis, it does not take much time to select scan flip-flops, but fault coverage is low. On the other hand, although the partial scan by testabilities generally results in high fault coverage, it requires more time to select scan flip-flops than the former method. In this paper, we analyzed and unified the strengths of the techniques by structural analysis and by testabilities. The new partial scan design technique not only reduces the time for selecting scan flip-flops but also improves fault coverage. Test results demonstrate the remarkable reduction of the time to select the scan flip-flops and high fault coverage in most ISCAS89 benchmark circuits.

• Journal of Distribution Science
• /
• v.11 no.10
• /
• pp.55-62
• /
• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.3
• /
• pp.12-36
• /
• 2023

Graph databases, which store different types of data and their relationships modeled as a graph, can be effective in managing and analyzing real estate spatial data linked by complex relationships. However, they are not widely used due to the limited spatial functionalities of graph databases. In this study, we propose a uniform grid-based real estate spatial data management approach using a graph database to respond to various real estate-related spatial questions. By analyzing the real estate community to identify relevant data and utilizing national point numbers as unit grids, we construct a graph schema that linking diverse real estate data, and create a test database. After building a test database, we tested basic topological relationships and spatial functions using the Jackpine benchmark, and further conducted query tests based on various scenarios to verify the appropriateness of the proposed method. The results show that the proposed method successfully executed 25 out of 29 spatial topological relationships and spatial functions, and achieved about 97% accuracy for the 25 functions and 15 scenarios. The significance of this study lies in proposing an efficient data integration method that can respond to real estate-related spatial questions, considering the limited spatial operation capabilities of graph databases. However, there are limitations such as the creation of incorrect spatial topological relationships due to the use of grid-based indexes and inefficiency of queries due to list comparisons, which need to be improved in follow-up studies.

• Journal of Korean Society of Steel Construction
• /
• v.23 no.4
• /
• pp.417-428
• /
• 2011

Depending on the plastic deformation capacity required, structural steel design under the current codes can be classified into three categories: elastic, plastic, and seismic design. Most of the current steel codes explicitly forbid the use of a steel material with a yield strength higher than 450 MPa in the plastic design because of the concerns about its low plastic deformation capacity as well as the lack of test data on local and lateral torsional buckling behavior. In this study, flexural tests on full-scale H-shape members built with SM490A (ordinary steel or benchmark material) and HSB800 (high-strength steel) were carried out. The primary objective was to investigate the appropriateness of extrapolating the local buckling criterion of the current codes, which was originally developed for normal-strength steel, to the case of high-strength steel. All the SM490A specimens performed consistently with the current code criteria and exhibited sufficient strength and ductility. The performance of the HSB800 specimens was also very satisfactory from the strength perspective; even the specimens with a noncompact and slender flange developed the plastic moment capacity. The HSB800 specimens, however, showed an inferior plastic rotation capacity due to the premature tensile fracture of the beam bottom flange beneath the vertical stiffener at the loading point. The plastic rotation capacity that was achieved was less than 3 (or the minimum level required for a plastic design). Although the test results in this study indicate that the extrapolation of the current flange local-buckling criterion to the case of high-strength steel is conservative from the elastic design perspective, further testing together with an associated analytical study is required to identify the causes of the tensile fracture and to establish a flange slenderness criterion that is more appropriate for high-strength steel.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.123-139
• /
• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of Korean Association for Spatial Structures
• /
• v.8 no.4
• /
• pp.47-55
• /
• 2008

This paper deals with basic theories and some numerical results on structural optimization for geodesic dome. First of all, the space efficiency of geodesic dome is investigated by using the ratio of icosahedron's surface area to the internal volume enclosed by it. The procedure how to create the geodesic dome is also provided in systematic way and implemented and utilized into the design optimization code ISADO-OPT. The mathematical programming technique is introduced to find out the optimum pattern of member size of geodesic dome against a point load. In this study, total weight of structure is considered as the objective function to be minimized and the displacement occurred at loading point and member stresses of geodesic dome are used as the constraint functions. The finite difference method is used to calculate the design sensitivity of objective function with respect to design variables. The SLP, SQP and MFDM available in the optimizer DoT is used to search optimum member size patterns of geodesic dome. It is found to be that the optimum member size pattern can be efficiently obtained by using the proposed design optimization technique and numerical results can be used as benchmark test as a basic reference solution for design optimization of dome structures.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.30 no.5
• /
• pp.405-413
• /
• 2017

In this paper, we study the biaxial buckling analysis of nonlocal MEE(magneto-electro-elastic) nano plates based on the first-order shear deformation theory. The in-plane electric and magnetic fields can be ignored for MEE(magneto-electro-elastic) nano plates. According to magneto-electric boundary condition and Maxwell equation, the variation of magnetic and electric potentials along the thickness direction of the MME plate is determined. In order to reformulate the elastic theory of MEE(magneto-electro-elastic) nano-plate, the nonlocal differential constitutive relations of Eringen is used. Using the variational principle, the governing equations of the nonlocal theory are discussed. The relations between nonlocal and local theories are investigated by computational results. Also, the effects of nonlocal parameters, in-plane load directions, and aspect ratio on structural responses are studied. Computational results show the effects of the electric and magnetic potentials. These computational results can be useful in the design and analysis of advanced structures constructed from MEE(magneto-electro-elastic) materials and may be the benchmark test for the future study.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.6
• /
• pp.115-121
• /
• 2015

In this paper, we proposed an iterative data-flow optimal scheduling algorithm based on genetic algorithm for high-performance multiprocessor. The basic hardware model can be extended to include detailed features of the multiprocessor architecture. This is illustrated by implementing a hardware model that requires routing the data transfers over a communication network with a limited capacity. The scheduling method consists of three layers. In the top layer a genetic algorithm takes care of the optimization. It generates different permutations of operations, that are passed on to the middle layer. The global scheduling makes the main scheduling decisions based on a permutation of operations. Details of the hardware model are not considered in this layer. This is done in the bottom layer by the black-box scheduling. It completes the scheduling of an operation and ensures that the detailed hardware model is obeyed. Both scheduling method can insert cycles in the schedule to ensure that a valid schedule is always found quickly. In order to test the performance of the scheduling method, the results of benchmark of the five filters show that the scheduling method is able to find good quality schedules in reasonable time.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.2
• /
• pp.1109-1117
• /
• 2014

We study free vibration analysis of sigmoid functionally graded materials(S-FGM) nano-scale plates, using a nonlocal elasticity theory of Eringen in this paper. This theory has ability to capture the both small scale effects and sigmoid function in terms of the volume fraction of the constituents for material properties through the plate thickness. Numerical solutions of S-FGM nano-scale plate are presented using this theory to illustrate the effect of nonlocal theory on natural frequency of the S-FGM nano-scale plates. The relations between nonlocal and local theories are discussed by numerical results. Further, effects of (i) power law index (ii) nonlocal parameters, (iii) elastic modulus ratio and (iv) thickness and aspect ratios on nondimensional frequencies are investigated. In order to validate the present solutions, the reference solutions are compared and discussed. The results of S-FGM nano-scale plates using the nonlocal theory may be the benchmark test for the free vibration analysis.

• Tunnel and Underground Space
• /
• v.31 no.6
• /
• pp.610-622
• /
• 2021

The DECOVALEX project is one of the representative international cooperative projects to enhance the understanding of the complex Thermo-Hydro-Mechanical-Chemical(THMC) coupled behavior in the high-level radioactive waste disposal system based on the numerical simulation. DECOVALEX-2023 is the current phase consisting of 7 tasks, and Task C aims to model the THM coupled behavior in the disposal system based on the Full-scale Emplacement (FE) experiment at the Mont-Terri underground rock laboratory. This study performs the numerical simulation based on the OGS-FLAC developed for the current study. In the numerical model, we emplaced the heater with constant power horizontally based on the FE experiment and monitored the pressure development, temperature increase, and mechanical deformation at the specific monitoring points. We monitored the capillary pressure as the primary effect inducing the flow in the buffer system, and thermal stress and pressurization were dominant in the surrounding rocks' area. The results will also be compared and validated with the other participating groups and the experimental data further.