• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.832-842
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• 2020

The coordination control of multiple Underactuated Underwater Vehicles (UUVs) moving in three dimensional space is investigated in this paper. The coordinated path following control task is decomposed into two sub tasks, that is, path following control and coordination control. In the spatial curve path following control task, path following error dynamics is build in the Serret-Frenet coordinate frame. The virtual reference object can be chosen freely on the desired spatial path. Considering the speed of the UUV, the line-of-sight navigation is introduced to help the path following errors quickly converge to zero. In the coordination control sub task, the communication topology of multiple UUVs is described by the graph theory. The speed of each UUV is adjusted to achieve the coordination. The path following system and the coordination control system are viewed as the feedback connection system. Input-to-state stable of the coordinated path following system can be proved by small gain theorem. The simulation experiments can further demonstrate the good performance of the control method.

• Analytical Science and Technology
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• v.18 no.5
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• pp.381-385
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• 2005

The title compound, $\{H_2NCH_2CH_2NH_2CH_2CH_2\}\{Cu(H_2O)_6\}(SO_4)_2$, I, has been synthesized under solvo/hydrothermal conditions and their crystal structure analyzed by X-ray single crystallography. Compound I crystallizes in the monoclinic system, $P2_1/n$ space group with a = 6.852(1), b = 10.160(2), $c=11.893(1){\AA}$, ${\beta}=92.928(8)^{\circ}$, $V=826.9(2){\AA}^3$, Z = 2, $D_x=1.815g/cm^3$, $R_1=0.031$ and ${\omega}R_2=0.084$. The crystal structure of the piperazine templated Cu(II)-sulfate demonstrate zero-dimensional compound constituted by doubly protonated piperazine cations, hexahydrated copper cations and sulfate anions. The central Cu atom has a elongated octahedral coordination geometry. The crystal structure is stabilized by three-dimensional networks of the intermolecular $O_{water}-H{\cdots}O_{sulfate}$ and $N_{pip}-H{\cdots}O_{sulfate}$ hydrogen bonds between the water molecules and sulfate anions and protonated piperazine cations. Based on the results of thermal analysis, the thermal decomposition reaction of compound I was analyzed to have three distinctive stages.

• Analytical Science and Technology
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• v.19 no.4
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• pp.309-315
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• 2006

Two piperazine-templated metal sulfate complexes, $(C_4N_2H_{12})[Ni(H_2O)_6](SO_4)_2$, I and ($C_4N_2H_{12}$) $[Co(H_2O)_6](SO_4)_2$, II, have been synthesized by hydro/solvothermal reactions and their crystal structures analyzed by single crystal X-ray diffraction methods. Complex I crystallizes in the monoclinic system, $P2_1/n$ space group, a=12.920(3), b=10.616(2), $c=13.303(2){\AA}$, ${\beta}=114.09(1)^{\circ}$, Z=4, $R_1=0.030$ for 3683 reflections; II: monoclinic $P2_1/n$, a=12.906(3), b=10.711(2), $c=13.303(2){\AA}$, ${\beta}=114.10(2)^{\circ}$, Z=4, $R_1=0.032$ for 4010 reflections. The crystal structures of the piperazine-templated metal(II) sulfates demonstrate zero-dimensional compound constituted by diprotonated piperazine cations, metal(II) cations and sulfate anions. The structures of complex I and II are substantially isostructural to that of the previously reported our piperazine-templated copper(II) sulfate complex $(C_4N_2H_{12})[Cu(H_2O)_6](SO_4)_2$. The central metal(II) atoms are coordinated by six water molecules in the octahedral geometry. The crystal structures are stabilized by three-dimensional networks of the $O_{water}-H{\cdots}O_{sulfate}$ and $N_{pip}-H{\cdots}O_{sulfate}$ hydrogen bonds between the water molecules and sulfate anions and protonated piperazine cations. Based on the results of thermal analysis, the thermal decomposition reactions of the complex I was analyzed to have three distinctive stages whereas the complex II proceed through several stages.

• Journal of the Korean institute of surface engineering
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• v.57 no.3
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• pp.214-220
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• 2024

In this study, three-dimensional (3D) networks structure using single-walled carbon nanotubes (SWCNTs) for Si-graphite composite electrode was developed and studied about effects on the electrochemical performances. To investigate the effect of SWCNTs on forming a conductive 3D network structure electrode, zero-dimensional (0D) carbon black and different SWCNTs composition electrode were compared. It was found that SWCNTs formed a conductive network between nano-Si and graphite particles over the entire area without aggregation. The formation of 3D network structure enabled to effective access for lithium ions leading to improve the c-rate performance, and provided cycle stability by alleviating the Si volume expansion from flexibility and buffer space. The results of this study are expected to be applicable to the electrode design for high-capacity lithium-ion batteries.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.6
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• pp.1001-1004
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• 1987

In this study mathematical properties of variational solution and solution of the boundary integral equation of the linear elasticity problem are studied. It is first reviewed that a variational solution for the three-dimensional linear elasticity problem exists in the Sobolev space [ $H^{1}$(.OMEGA.)]$^{3}$ and, then, it is shown that a unique solution of the boundary integral equation is identical to the variational solution in [ $H^{1}$(.OMEGA.)]$^{3}$. To represent the boundary integral equation, the Green's formula in the Sobolev space is utilized on the solution domain excluding a ball, with small radius .rho., centered at the point where the point load is applied. By letting .rho. tend to zero, it is shown that, for the linear elasticity problem, boundary integral equation is valid for the variational solution. From this fact, one can obtain a numerical approximatiion of the variational solution by the boundary element method even when the classical solution does not exist.exist.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.285-298
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• 2022

Continuous shrinkage priors, as well as spike and slab priors, have been widely employed for Bayesian inference about sparse regression coefficient vectors or covariance matrices. Continuous shrinkage priors provide computational advantages over spike and slab priors since their model space is substantially smaller. This is especially true in high-dimensional settings. However, variable selection based on continuous shrinkage priors is not straightforward because they do not give exactly zero values. Although few variable selection approaches based on continuous shrinkage priors have been proposed, no substantial comparative investigations of their performance have been conducted. In this paper, We compare two variable selection methods: a credible interval method and the sequential 2-means algorithm (Li and Pati, 2017). Various simulation scenarios are used to demonstrate the practical performances of the methods. We conclude the paper by presenting some observations and conjectures based on the simulation findings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.618-627
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• 2002

In processing images using 2 dimensional Discrete Wavelet Transform(2D-DWT), the method to process the pixels around the image boundary may affect the quality of image and the cost to implement in hardware and software. This paper proposed an effective method to treat the boundary pixels, which is apt to implement in hardware and software without losing the quality of the image costly. This method processes the 2-D image as 1-D array so that 2-D DWT is performed by considering the image with the serial-sequential data structure (Serial-Sequential Processing). To show the performance and easiness in implementation of the proposed method, an image compression codec which compresses image and reconstructs it has been implemented and experimented. It included log-scale fried quantizer, but the entropy coder was not implemented. From the experimental results, the proposed method showed the SNR of almost the same SNR(Signal to Noise Ratio) to the Periodic Expansion(PE) method when the compression ratio(excluding entropy coding) of 2:1, 15.3% higher than Symmetric Expansion(SE) method, and 9.3% higher than 0-pixel Padding Expansion(ZPE) method. Also PE method needed 12.99% more memory space than the proposed method. By considering only the compression process, SE and ZPE methods needed additional operations than the proposed one. In hardware implementation, the proposed method in this paper had 5.92% of overall circuit as the control circuit, while SE, PE, and ZPE method has 22%, 21,2%, and 11.9% as the control circuit, respectively. Consequently, the proposed method can be thought more effective in implementing software and hardware without losing any image quality in the usual image processing applications.

• 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].