• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.321-328
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• 2018

In clinical trials with repeated measurements, the time-averaged difference (TAD) may provide a more powerful evaluation of treatment efficacy than the rate of changes over time when the treatment effect has rapid onset and repeated measurements continue across an extended period after a maximum effect is achieved (Overall and Doyle, Controlled Clinical Trials, 15, 100-123, 1994). The sample size formula has been investigated by many researchers for the evaluation of TAD in two treatment groups. For the evaluation of TAD in multi-arm trials, Zhang and Ahn (Computational Statistics & Data Analysis, 58, 283-291, 2013) and Lou et al. (Communications in Statistics-Theory and Methods, 46, 11204-11213, 2017b) developed the sample size formulas for continuous outcomes and count outcomes, respectively. In this paper, we derive a sample size formula to evaluate the TAD of the repeated binary outcomes in multi-arm trials using the generalized estimating equation approach. This proposed sample size formula accounts for various correlation structures and missing patterns (including a mixture of independent missing and monotone missing patterns) that are frequently encountered by practitioners in clinical trials. We conduct simulation studies to assess the performance of the proposed sample size formula under a wide range of design parameters. The results show that the empirical powers and the empirical Type I errors are close to nominal levels. We illustrate our proposed method using a clinical trial example.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2806-2808
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• 2010

The structure of 3-aminophenol $(CO_2)_1$ cluster was computationally studied both in the ground and the lowest singlet excited electronic states. The ground state structure and binding energy of the cluster was investigated using the second-order M$\ddoot{o}$ller-Plesset perturbation theory (MP2) at the complete basis set (CBS) limit. The excited state geometry of the cluster was obtained at the second-order approximate coupled cluster (CC2) level with cc-pVDZ basis set, and the $S_0-S_1$ absorption spectrum was simulated by calculating Franck-Condon overlap integral. The ground state geometry of the global minimum with a very high binding energy of 4.3 kcal/mol was found for the cluster, due to the interaction between amino group and $CO_2$ in addition to the strong $\pi-\pi$ interaction between the aromatic ring and $CO_2$. The excited state geometry shows a very big shift in the position of $CO_2$ compared to the ground state geometry, which results in low intensity and broad envelope in the Franck-Condon simulation.

• Communications of the Korean Mathematical Society
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• v.16 no.4
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• pp.679-690
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• 2001

Doubly stochastic matrices are n$\times$n nonnegative ma-trices whose row and column sums are all 1. Convex polytope $\Omega$$_{n}$ of doubly stochastic matrices and more generally (R,S), so called transportation polytopes, are important since they form the domains for the transportation problems. A theorem by Birkhoff classifies the extremal matrices of , $\Omega$$_{n}$ and extremal matrices of transporta-tion polytopes (R,S) were all classified combinatorially. In this article, we consider signed version of $\Omega$$_{n}$ and (R.S), obtain signed Birkhoff theorem; we define a new class of convex polytopes (R,S), calculate their dimensions, and classify their extremal matrices, Moreover, we suggest an algorithm to express a matrix in (R,S) as a convex combination of txtremal matrices. We also give an example that a polytope of signed matrices is used as a domain for a decision problem. In this context of finite reflection(Coxeter) group theory, our generalization may also be considered as a generalization from type $A_{*}$ n/ to type B$_{n}$ D$_{n}$. n/.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.17-35
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• 2011

The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

• Journal of the Korean Chemical Society
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• v.66 no.3
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• pp.185-193
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• 2022

The theoretical investigation has been performed to predict thermodynamic stability, density, detonation velocity, and detonation pressure of energetic salts produced by pairing of nitrogen-rich anions (tetrazine, oxadiazole etc.) and cations (NH₃OH⁺, NH₂NH₃⁺, CH₉N₆⁺, C₂H₆N₅⁺). All possible geometries and the binding energy for the trigger bond of energetic salts have been optimized at the B3LYP/cc-pVDZ level of theory. The detonation velocity and detonation pressure have been calculated using Kamlet-Jacobs equation, while enthalpy has been predicted at the G2MP2 level of theory. The predicted results reveal that the energetic salts including small sized NH₃OH⁺(1) and NH₂NH₃⁺(2) cations increase detonation property. And also the energetic salts including more amino group (-NH₂) such as CH₉N₆⁺(3) cation increase thermodynamic stability. These results provide basic information for the development the high energy density materials (HEDMs).

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.70-77
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• 2014

Collaborative processes among team members including communication, coordination, and information-handling processes either during pre-construction or project execution are required in order to accomplish the objectives of construction projects. However, current construction management practice does not explicitly take the effect of organizational aspects on project performance into account. This paper introduces a method to understand collaborative processes in an explicit and systematic fashion. An agent-based simulation of collaborative working processes within construction project teams was designed from game theory perspective and implemented. The simulation produced both individual behavior and network dynamics. Individuals represented as agents made efforts to improve performance by communication and coordinating with other members, and overall team network was emerged as a result of interactions among members. Interestingly, it was found that the tendency of forming cohesive subgroups increased when sustaining relations with between-group partners incurs higher cost. The primary contribution of this paper is that it presented an explicit approach to examining collaborative working processes in construction project teams and it extended existing computational organization and network studies by integrating individual behavior models and network models.

• Atmosphere
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• v.17 no.4
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• pp.315-326
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• 2007

The effects of windbreaks on the reduction of suspended particles are investigated using a computational fluid dynamics (CFD) model with the ${\kappa}-{\varepsilon}$ turbulence closure scheme based on the renormalization group (RNG) theory. In the control experiment, the recirculation zones behind the storage piles are generated and, as a whole, relatively monotonous flow patterns appear. When the windbreaks with the 0% porosity are constructed, the recirculation zones are generated by the windbreaks and very complicated flow patterns appear due to the interference between the windbreaks and storage piles. The porosity of the windbreaks suppresses the generation of the recirculation zone and decreases the wind velocity in the windbreaks as well as that outside the windbreaks. As the emission of suspended particles from the storage piles are closely related with the friction velocity at the surfaces of the storage piles, variation of the friction velocity and total amount of the emission of the suspended particles with the height and porosity of the windbreaks are investigated. The results show that higher and more porous windbreaks emit less suspended particles and that the reduction effect of the porosity is still more effective than that of the height. In the case of the windbreak with 30 m height and 50% porosity, friction velocities above the storage piles are smaller than the critical friction velocity above which particles would be suspended. As a result, total amount of suspended particles are much fewer than those in other cases.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.9
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• pp.923-932
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• 2011

Because of the instability of a flow pattern in the inlet transition square duct (hereinafter referred to as "transition duct") of a heat recovery steam generator (hereinafter referred to as "HRSG") in a combined cycle power plant, the Reynolds number in the first row of a tube bank is differs sharply from that in the sectional area of the transition duct. This causes differences in the heat flux in each tube in the tube bank. The computational fluid dynamics (CFD) predictions provide three-dimensional results for velocity, temperature, and other flow parameters over the entire domain of the duct and HRSG. A renormalization group theory (RNG) based k-${\epsilon}$�� turbulent model is used for obtaining the results cited in this study. A porous media option is used for modeling the tube banks and the number of transfer units method is used for determining the heat transfer characteristics. This study describes a comparison between the numerical simulation results and actual design output.

• Nuclear Engineering and Technology
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• v.18 no.2
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• pp.78-84
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• 1986

An equation of material number density sensitivity coefficient is derived using first-order perturbation theory. The beginning of cycle of Super-Phenix I is taken as the reference system for this study. Effective multiplication factor of the reference system is defined as system response function and fuel enrichment and fuel effective density are chosen for the variation of reference input data since they are described by material number density which is a component of Boltzmann operator. The nuclear computational code system (KAERI-26 group cross section library/1DX/2DB/PERT-V) is employed for this calculation. Sensitivity coefficient of fuel enrichment on effective multiplication factor is 4.576 and sensitivity coefficient of effective fuel density on effective multiplication factor is 0.0756. This work shows that sensitivity methodology is lesser timeconsuming and gives more informations on important design parameters in comparison with the direct iterative calulation through large computer codes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].