• Smart Structures and Systems
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• v.23 no.6
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• pp.565-577
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• 2019

One of the most effective countermeasures for mitigating cable vibration is to install mechanical dampers near the anchorage of the cable. Most of the dampers used in the field are so-called passive dampers where their parameters cannot be changed once designed. The parameters of passive dampers are usually determined based on the optimal damper force obtained from the universal design curve for linear dampers, which will provide a maximum additional damping for the cable. As the optimal damper force is chosen based on a predetermined principal vibration mode, passive dampers will be most effective if cable undergoes single-mode vibration where the vibration mode is the same as the principal mode used in the design. However, in the actual engineering practice, multi-mode vibrations are often observed for cables. Therefore, it is desirable to have dampers that can suppress different modes of cable vibrations simultaneously. In this paper, MR dampers are proposed for controlling multi-mode cable vibrations, because of its ability to change parameters and its adaptability of active control without inquiring large power resources. Although the highly nonlinear feature of the MR material leads to a relatively complex representation of its mathematical model, effective control strategies can still be derived for suppressing multi-mode cable vibrations based on nonlinear modelling, as proposed in this paper. Firstly, the nonlinear Bouc-wen model is employed to accurately portray the salient characteristics of the MR damper. Then, the desired optimal damper force is determined from the universal design curve of friction dampers. Finally, the input voltage (current) of MR damper corresponding to the desired optimal damper force is calculated from the nonlinear Bouc-wen model of the damper using a piecewise linear interpolation scheme. Numerical simulations are carried out to validate the effectiveness of the proposed control algorithm for mitigating multi-mode cable vibrations induced by different external excitations.

• English & American cultural studies
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• v.14 no.2
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• pp.251-285
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• 2014

Monsters cannot speak. They have been objectified and represented through a particular concept 'monstrosity' that renders the presence of monsters effectively simplified and nullified. In contemporary monster narratives, however, the site of monsters reveals that they could be the complex construction of society, culture, language and ideology. As going into the structure that concept is based on, therefore, meanings of monsters would be seen to be highly unstable. When symbolic language strives to match monsters with a unified concept, their meanings become only further deferred rather than valorized. This shows the language of monsters should disclose the self-contradiction inherent in 'monstrosity,' which has made others—namely beings we define as 'different' from ourselves in culture or physical appearance—embodied as abject and horrifying monsters. Unable to be understood, accepted, or called humans. I analyse Frankenstein and Dracula that firmly converge monstrous bodies into a symbolic meaning, demonstrating how this fusion causes problems in the multicultural society. I especially emphasize the undeniable affirmation of expurgated others we need to have empathetic relations with, because their difference, unfamiliarity, and slight divergences are likely to be defined as abnormalities. In the multicultural society, thus, we must learn to embrace diversity, while also having to recognize there are many others that have been thought of as monsters; ironically enabling us to think about an undeniable imperative of being responsive to other people. In this respect, the monstrous inhuman goes to the heart of the ethical undercurrent of multiculturalism, its resolute attempt to recognize and respect someone else's difference from me. A focus on empathetic relations with others, thus, can strengthen the process of creating social mechanisms that do justice to the competing claims of different cultural groups and individuals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2112-2124
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• 2023

With the rise of economic and safety standards for nuclear reactors, new concepts of Gen-IV reactors and modular reactors showed more complex designs that challenge current tools for reactor physics analysis. A Monte Carlo (MC) two-step method was proposed in this work. This calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections from heterogeneous models. The multi-group MC method, which can adapt locally-heterogeneous models, is used in the core calculation step. This calculation scheme is verified using a Gen-IV modular lead-based fast reactor (LFR) benchmark case. The influence of homogenized patterns, scatter approximations, flux separable approximation, and local heterogeneity in core calculation on simulation results are investigated. Results showed that the cross-sections generated using the 3D assembly model with a locally heterogeneous representation of control rods lead to an accurate estimation with less than 270 pcm bias in core reactivity, 0.5% bias in control rod worth, and 1.5% bias on power distribution. The study verified the applicability of multi-group cross-sections generated with the MC method for LFR analysis. The study also proved the feasibility of multi-group MC in core calculation with local heterogeneity, which saves 85% time compared to the continuous-energy MC.

• Journal of English Language & Literature
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• v.58 no.5
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• pp.859-880
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• 2012

This paper aims at analyzing Robert Southey's Thalaba the Destroyer in relation to cultural colonialism of the British Romantic period and investigating the ways in which this text portrays the Other through its literary representation of the East. Especially, this paper attempts to show that the Oriental world constructed in Southey's text reveals the imperial subject's self-conscious awareness of its unstable relation with the unknown Other. For this purpose, this paper attends to the formal aspects of Thalaba the Destroyer, examining the process by which the reader's generic expectations about the "epic" undergo complex revisions and frustrations through reading this text. The epic elements contained in Thalaba the Detroyer include the battle between good and evil and the hero's moral epiphany arising from his struggle against malicious enemies. Yet, Thalaba the Destroyer constantly destabilizes the distinction between self and other by leading the reader to recognize the uncomfortable similarity between the poem's tyrannical figures and imperialistic monarchs in the Western civilization. Thus, when the hero enacts a revolution against despotism, the resistant power points not only to the imagined false kingdom within the text, but to the core of the real Empire that seeks to construct its own "garden" in the global scene. In addition, Southey's "panoramic" description of Oriental objects and stories in his footnotes lacks a framing perspective, erasing and de-stabilizing subject/object distinctions. In these footnotes, he exposes his profound attraction to the culture of "Other" and also conveys his aspiration to transforming Eastern myths and stories into profitable literary texts. Southey's attitude to the East in the footnotes appears to be partially grounded upon the interest of mercantile capitalists of the West, who need to discover potential commodities. Yet, simultaneously, he reveals a sense of moral hesitation about his own desire for the materiality of the East, along with deep anxiety arising from the fear of punishment.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.89-96
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• 2023

In this paper, we propose a GPU-based method for real-time processing of dynamic re-meshing required for tearing cloth. Thin shell materials are used in various fields such as physics-based simulation/animation, games, and virtual reality. Tearing the fabric requires dynamically updating the geometry and connectivity, making the process complex and computationally intensive. This process needs to be fast, especially when dealing with interactive content. Most methods perform re-meshing through low-resolution simulations to maintain real-time, or rely on an already segmented pattern, which is not considered dynamic re-meshing, and the quality of the torn pattern is low. In this paper, we propose a new GPU-optimized dynamic re-meshing algorithm that enables real-time processing of high-resolution fabric tears. The method proposed in this paper can be used for virtual surgical simulation and physics-based modeling in games and virtual environments that require real-time, as it allows dynamic re-meshing rather than pre-split meshes.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.177-188
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• 2024

As technology evolves, Internet usage continues to grow, resulting in a geometric increase in network traffic and communication volumes. The network path selection process, which is one of the core elements of the Internet, is becoming more complex and advanced as a result, and it is important to effectively manage and analyze it, and there is a need for a representation and visualization method that can be intuitively understood. To this end, this study designs a framework that analyzes network data using BGP, a network path selection method, and applies it to the cyber common operating picture for situational awareness. After that, we analyze the visualization elements required to visualize the information and conduct an experiment to implement a simple visualization. Based on the data collected and preprocessed in the experiment, the visualization screens implemented help commanders or security personnel to effectively understand the network situation and take command and control.

• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.1-16
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• 2024

Due to its complexity and high diagnosis and treatment costs, heart attack (HA) is the top cause of death globally. Heart failure's widespread effect and high morbidity and death rates make accurate and fast prognosis and diagnosis crucial. Due to the complexity of medical data, early and accurate prediction of HA is difficult. Healthcare providers must evaluate data quickly and accurately to intervene. This novel hybrid approach predicts HA using Long Short-Term Memory (LSTM) networks, Deep belief networks (DBNs) with attention mechanism, and robust data mining to fill this essential gap. HA is predicted using Kaggle, PhysioNet, and UCI datasets. Wearable sensor data, ECG signals, and demographic and clinical data provide a solid analytical base. To maintain consistency, ECG signals are normalized and segmented after thorough cleaning to remove missing values and noise. Feature extraction employs complex approaches like Principal Component Analysis (PCA) and Autoencoders to pick time-domain (MNN, SDNN, RMSSD, PNN50) and frequency-domain (PSD at VLF, LF, HF bands) characteristics. The hybrid model architecture uses LSTM networks for sequence learning and DBNs for feature representation and selection to create a robust and comprehensive prediction model. Accuracy, precision, recall, F1-score, and ROC-AUC are measured after cross-entropy loss and SGD optimization. The LSTM-DBN model outperforms predictive methods in accuracy, sensitivity, and specificity. The findings show that several data sources and powerful algorithms can improve heart attack predictions. The proposed architecture performed well on many datasets, with an accuracy rate of 96.00%, sensitivity of 98%, AUC of 0.98, and F1-score of 0.97. High performance proves this system's dependability. Moreover, the proposed approach is outperformed compared to state-of-the-art systems.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.4
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• pp.91-100
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• 2008

Numerical implementation with a Cartesian cut-cell method is conducted in this study. A Cartesian cut-cell method is an easy and efficient mesh generation methodology for complex geometries. In this method, a background Cartesian grid is employed for most of computational domain and a cut-cell grid is applied for the peculiar grids where the flow characteristics are changed such as solid boundary to enhance the accuracy, applicability and efficiency. Accurate representation of complex geometries can be obtained by using the cut-cell method. The cut-cell grids are constructed with irregular meshes which have various shape and size. Therefore, the finite volume method is applied to numerical discretization on a irregular domain. The HLLC approximate Riemann solver, a Godunov-type finite volume method, is employed to discretize the advection terms in the governing equations. The weighted average flux method applied on the Cartesian cut cell grid for stabilization of the numerical results. To validate the numerical model using the Cartesian cut-cell grids, the model is applied to the rectangular tank problem of which the exact solutions exist. As a comparison of numerical results with the analytical solutions, the numerical scheme well represents flow characteristics such as free surface elevation and velocities in x-and y-directions in a rectangular tank with the Cartesian and cut-cell grids.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.97-105
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• 2005

In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.