• Structural Engineering and Mechanics
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• v.22 no.5
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• pp.599-611
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• 2006

The theory with hierarchical warping functions had been used to analyze composite thin-walled structure, laminated beam and had good results. In the present paper, a series of hierarchical warping functions are developed to analyze the cylindrical bending problems of composite lamina. These warping functions which refine through-the-thickness variation of displacements were composed of basic and corrective functions by taking into account of anisotropic, material discontinues, and transverse shear and normal strain. Then the hierarchical finite element method was used to form a numerical algorithm. The distribution of the displacements, in-plane stresses, transverse shear stresses and transverse normal stress for composite laminate were analyzed with the present model. The results show that the present model has precise mechanical response compared with the first deformation transverse theory and the corrective order affects the accuracy of result.

• IE interfaces
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• v.19 no.1
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• pp.34-42
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• 2006

This paper presents a scheme for a hierarchical production scheduling and control system for a refrigerator factory with mixed model assembly lines. The setting of the factory is as follows. There are three mixed-model assembly lines called main line A, B and C and two batch lines that supply parts to the main lines. For each of the main lines, three work-centers are dedicated to them. The sub-lines and work-centers produce parts in batch type. An incoming production order from the master planner is characterized by its product type, amount, and due date. Under this situation, the proposed scheme has several features to schedule and control the above mentioned factory; 1) select the starting time and the place (assembly line) for an order processing, 2) devise a way to control orders to be processed as scheduled, and 3) reschedule orders when something unexpected happen. Finally, this paper provides a case study where the proposed scheme is applied to.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1595-1607
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• 2018

In this paper, a hierarchical control strategy is introduced to control a new three-port multidirectional DC-DC converter for integrating an energy storage system (ESS) to a bipolar DC microgrid (BPDCMG). The proposed converter provides a voltage-balancing function for the BPDCMG and adjusts the states of charge (SoC) of the ESS. Previous studies tend to balance the voltage of the BPDCMG buses with active sources or by transferring power from one bus to another. Furthermore, the batteries available in BPDCMGs were charged equally by both buses. However, this power sharing method does not guarantee efficient operation of the whole system. In order to achieve a higher efficiency and lower energy losses, a triple-layer hierarchical control strategy, including a primary droop controller, a secondary voltage restoration controller and a tertiary optimization controller are proposed. Thanks to the multi-functional operation of the proposed converter, its conversion stages are reduced. Furthermore, the efficiency and weight of the system are both improved. Therefore, this converter has a significant capability to be used in portable BPDCMGs such as electric DC ships. The converter modes are analyzed and small-signal models of the converter are extracted. Comprehensive simulation studies are carried out and a BPDCMG laboratory setup is implemented in order to validate the effectiveness of the proposed converter and its hierarchical control strategy. Simulation and experimental results show that using the proposed converter mitigates voltage imbalances. As a result, the system efficiency is improved by using the hierarchical optimal power flow control.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.149-169
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• 2015

This study tried to find out how to overcome multicollinearity problems in the structural equation model by creating a hierarchical construct model about the repurchase intention of social commerce. This study selected, as independent variables, price, quality, service, and social influence, based on literature review about social commerce, and then, as detailed variables of independent variables, selected system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norms, and reputation. As results of empirical analysis about hierarchical construct model, all the independent variables were accepted having a significant impact on repurchase intention of social commerce. Next, this study analyzed the competition model that eight independent variables of price, system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norm, and reputation directly influence the repurchase intention of social commerce. As results of empirical analysis, system quality, information quality, transaction safety, communication appeared to be insignificant. This study showed that hierarchical construct model is useful to overcome the multicollinearity problem in structural equational model and to increase explanatory power.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.2
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• pp.199-205
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• 2004

This paper describes the fault diagnosis method to order to construct CIM in complex system with hierarchical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement a special neural network. Fault diagnosis system can forecast faults in a system and decide from the signal information of current machine state. Comparing with other diagnosis system for a single fault, the developed system deals with multiple fault diagnosis, comprising hierarchical neural network (HNN). HNN consists of four level neural network, i.e. first is fault symptom classification and second fault diagnosis for item, third is symptom classification and forth fault diagnosis for component. UNIX IPC is used for implementing HNN with multitasking and message transfer between processes in SUN workstation with X-Windows (Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural network represents a separate process in UNIX operating system, information exchanging and cooperating between each neural network was done by message queue.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.29-40
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• 2000

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.5-12
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• 2000

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution and it is shown to be useful in such Bayesian meta-analysis. A general class of skewed elliptical distribution is reviewed and developed. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierarchical selection model and use Markov chain Monte Carlo methods to develop inference for the parameters of interest.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.175-184
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• 2002

In this paper, we proposed separate queue scheme in each hierarchical cell for effective use of wireless channel. This method reduces the blocking rata of high speed mobile station's handoff in hierarchical cellular systems. Basically for the high speed mobile stations channels are allocated in macrocell and for the low speed mobile stations channels are allocated in microcell. In order to reduce the rate of forced handoff termination, some reservation channels are employed for the fast handoff calls in the macrocells. And the queue is located in each cell to be able to store handoff requests and takeback requests. The overflowed mobile station are able to perform takeback as soon as a corresponding channel is available.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.17-20
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• 2008

A clustering scheme for ad hoc networks is aimed at managing a number of mobile devices by utilizing hierarchical structure of the networks. In order to construct and maintain an effective hierarchical structure in ad hoc networks where mobile devices may move at high mobility, the following requirements must be satisfied. The role of each mobile device for the hierarchical structure is adaptive to dynamic change of the topology of the ad hoc networks. The role of each mobile device should thus change autonomously based on the local information. The overhead for management of the hierarchical structure is small. The number of mobile devices in each cluster should thus be almost equivalent. This paper proposes an adaptive multihop clustering scheme for highly mobile ad hoc networks. The results obtained by extensive simulation experiments show that the proposed scheme does not depend on mobility and node degree of mobile devices in the ad hoc network, which satisfy the above requirements.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.161-175
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• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.