• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.45-50
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• 2010

This paper explores a new approach for modeling of decision-making problems that involve uncertain, time-dependent and sequence-dependent processes which can be applied to semiconductor industry. In the proposed approach, which is based on probability theory, approximate sample paths are required to be specified by probability and statistic characteristics. Completely specified sample paths are seen to be elementary and fundamental outcomes of the related experiment. The proposed approach is suitable for modeling real processes more accurately. A case study is applied to a single item production planning problem with continuous and uncertain demand and the solution obtained by the approximate path specification method shows less computational efforts and practically desirable features. The application possibility and general plan of the proposed approach in semiconductor manufacturing process is also described in the paper.

• Asia Marketing Journal
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• v.18 no.4
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• pp.27-49
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• 2017

The two competing underlying mechanisms of anchoring, anchoring-and-adjustment and selective accessibility, have very different managerial implications for the effect of price as an anchor on willingness-to-pay (WTP). To clarify their relative roles in inducing the anchoring effect, path analysis modeling in which two paths are included in a single model was utilized. The first path proceeds directly from anchor price to WTP, representing anchor-and-adjustment. The second path, representing selective accessibility, includes a mediator formed by various explanatory variables of WTP. The results consistently show that only the direct path, anchoring-and-adjustment, is significant. The results also show that the level of available product information has no significant moderation effect on both of the paths, which implies the robustness of the result with respect to information level.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.652-654
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• 2023

The accurate prediction of User Equipment (UE) paths in wireless networks is crucial for improving handover mechanisms and optimizing network performance, particularly in the context of Beyond 5G and 6G networks. This paper presents a comprehensive evaluation of unidirectional and bidirectional recurrent neural network (RNN) architectures for UE path prediction. The study employs a sequence-to-sequence model designed to forecast user paths in a wireless network environment, comparing the performance of unidirectional and bidirectional RNNs. Through extensive experimentation, the paper highlights the strengths and weaknesses of each RNN architecture in terms of prediction accuracy and computational efficiency. These insights contribute to the development of more effective predictive path-based mobility management strategies, capable of addressing the challenges posed by ultra-dense cell deployments and complex network dynamics.

• Korean Journal of Materials Research
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• v.25 no.9
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• pp.429-434
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• 2015

Resistance switching memory cells were fabricated using atomically dispersed Pt-$SiO_2$ thin film prepared via RF co-sputtering. The memory cell can switch between a low-resistance-state and a high-resistance-state reversibly and reproducibly through applying alternate voltage polarities. Percolated conducting paths are the origin of the low-resistance-state, while trapping electrons in the negative U-center in the Pt-$SiO_2$ interface cause the high-resistance-state. Intermediate resistance-states are obtained through controlling the compliance current, which can be applied to multi-level operation for high memory density. It is found that the resistance value is related to the capacitance of the memory cell: a 265-fold increase in resistance induces a 2.68-fold increase in capacitance. The exponential growth model of the conducting paths can explain the quantitative relationship of resistance-capacitance. The model states that the conducting path generated in the early stage requires a larger area than that generated in the last stage, which results in a larger decrease in the capacitance.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.7
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• pp.789-795
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• 2011

In elliptical vibration cutting (EVC), cutting performance is largely affected by the shape of an elliptical path of the cutting tool. In this study, two parallel piezoelectric actuators were used to make an elliptical vibration cutting device. When harmonic voltages of $90^{\circ}$ out-of-phase are supplied to the EVC device, creation of an ideal elliptical trajectory whose major and minor axes are parallel to the cutting and thrust directions is anticipated from a kinematic analysis of the EVC device, however, the paths we experimentally observed showed significant distortions in its shape ranging from skew to excessive elongation of the major axis of the ellipse. To compensate distortions, an analytical model describing the elliptical path of the cutting tool was developed and verified with experimental results, and based on the analytical model, the distorted elliptical paths created at 100 Hz, 1 kHz, and 16 kHz were corrected for skew and elongation.

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.711-724
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• 2012

The goal of this study is to conceptually orientate optimized layouts of outrigger belt trusses which are in widespread use today in the design of tall buildings by strut-and-tie truss models utilizing a topology optimization method. In this study unknown strut-and-tie models are realized by using a typical SIMP method of topology optimization methods. In tradition strut-and-tie model designs find the appropriate strut-and-tie trusses along force paths with respect to elastic stress distribution, and then engineers or designers determine the most proper truss models by experience and intuition. It is linked to a trial-and-error procedure based on heuristic strategies. The presented strut-and tie model design by using SIMP provides that belt truss models are automatically and robustly produced by optimal layout information of struts-and-ties conforming to force paths without any trial-and-error. Numerical applications are studied to verify that outrigger belt trusses for tall buildings are optimally chosen by the proposed method for both static and dynamic responses.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.287-294
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• 2005

Flow rate measurement uncertainties of the ultrasonic flow meter are generally influenced by many different factors, such as Reynolds number, flow distortion, turbulence intensity, wall surface roughness, velocity integration method along the acoustic paths, and transducer installation method, etc. Of these influencing factors, one of the most important uncertainties comes from the velocity integration method. In the present study, a optimization weighting factor method for 5-chord, which is given by a function of the chord locations of acoustic paths, is employed to obtain the mean velocity in the flow through a pipe. The power law profile is assumed to model the axi-symmetric pipe flow and its results are compared with the present weighting factor concept. For an asymmetric pipe flow, the Salami flow model is applied to obtain the velocity profiles. These theoretical methods are also compared with the previous Gaussian, Chebyshev, and Tailor methods. The results obtained show that for the fully developed turbulent pipe flows with surface roughness effects, the present weighting factor method is much less sensitive than Chebyshev and Tailor methods, leading to a better reliability in flow rate measurement using the ultrasonic flow meters.

• The Korean Journal of Rehabilitation Nursing
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• v.15 no.1
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• pp.20-29
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• 2012

Purpose: The purpose of this study was to explore factors affecting uncertainty and general well-being based on Uncertainty in Illness Theory. Methods: Data were collected from 125 outpatients who had received hemodialysis. The path model among four concepts, such as period of hemodialysis, social support, uncertainty, and general well-being, was tested. Tangible support, positive social interaction, affectionate, and emotional/informational support were measured as social support. Adaptation in the model was operationalized as general well-being which consisted of anxiety, depression, positive well-being, self-control, and general health. Results: All paths were statistically significant at the level of ${\alpha}$=.05. The significant paths were the path from period of hemodialysis to uncertainty (t=-2.86), social support to uncertainty (t=-2.01), uncertainty to general wellbeing (t=-2.85), and social support to general well-being (t=3.55). Conclusion: Patients who perceived low uncertainty and high social support were likely to feel well-being. Therefore, nurses should give patients appropriate information according to their needs and have meaningful interaction with patients to reduce their uncertainty and render social support.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.3
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• pp.103-110
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• 2013

Logical Effort [1, 2] is a simple hand-calculated method that measures quick delay estimation. It has the advantage of reducing the design cycle time. However, it has shortcomings in designing a path for minimum area or power under a fixed-delay constraint. The method of overcoming the shortcomings is shown in [3], but it is constrained for a single logical path. This paper presents an advanced gate sizing method in multiple logical paths based on the equal delay model. According to the results of the simulation, the power dissipation for both the existing logical effort method and proposed method is almost equal. However, compared with the existing logical effort method, it is about 52 (%) more efficient in space.

• Nuclear Engineering and Technology
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• v.39 no.4
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• pp.337-348
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• 2007

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.