• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.196-202
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• 2024

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease prediction. Due to breast cancer's favorable prognosis at an early stage, a model is created to utilize the Dataset on Wisconsin Diagnostic Breast Cancer (WDBC). Conversely, this model's overarching axiom is to compare the effectiveness of five well-known ML classifiers, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), and Naive Bayes (NB) with the conventional method. To counterbalance the effect with conventional methods, the overarching tactic we utilized was hyperparameter tuning utilizing the grid search method, which improved accuracy, secondary precision, third recall, and finally the F1 score. In this study hyperparameter tuning model, the rate of accuracy increased from 94.15% to 98.83% whereas the accuracy of the conventional method increased from 93.56% to 97.08%. According to this investigation, KNN outperformed all other classifiers in terms of accuracy, achieving a score of 98.83%. In conclusion, our study shows that KNN works well with the hyper-tuning method. These analyses show that this study prediction approach is useful in prognosticating women with breast cancer with a viable performance and more accurate findings when compared to the conventional approach.

• Cartoon and Animation Studies
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• s.49
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• pp.697-712
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• 2017

In recent years, film and animation for cinematic release have embraced stereoscopic vision and the three-dimensional depth it creates for the viewer. The maturation of consumer-level virtual reality (VR) technology simultaneously spurred a wave of media productions set within 3D space, ranging from computer games to pornographic videos, to Academy Award-nominated animated VR short film Pearl. All of these works rely on stereoscopic fusion through stereopsis, that is, the perception of depth produced by the brain from left and right images with the amount of binocular parallax that corresponds to our eyes. They aim to emulate normal human vision. Within more experimental practices however, a fully rendered 3D space might not always be desirable. In my own abstract animation work, I tend to favour 2D flatness and the relative obfuscation of spatial relations it affords, as this underlines the visual abstraction I am pursuing. Not being able to immediately understand what is in front and what is behind can strengthen the desired effects. In 2015, Jeffrey Shaw challenged me to create a stereoscopic work for Animamix Biennale 2015-16, which he co-curated. This prompted me to question how stereoscopy, rather than hyper-defining space within three dimensions, might itself be used to achieve a confusion of spatial perception. And in turn, how abstract and experimental moving image practices can benefit from stereoscopy to open up new visual and narrative opportunities, if used in ways that break with, or go beyond stereoscopic fusion. Noteworthy works which exemplify a range of non-traditional, expanded approaches to binocular vision will be discussed below, followed by a brief introduction of the stereoscopic animation loop III=III which I created for Animamix Biennale. The techniques employed in these works might serve as a toolkit for artists interested in exploring a more experimental, expanded engagement with stereoscopy.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.207-213
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• 2008

For decades, we have filled our theme parks, shopping malls, a streets and etc. with complementary or competing medias. These spaces have remedied newspapers, magazines, radio, TV and film or have been the object for remediation. Because there has been no remediation in traditional theatrical stage design, many problems come along with the design, which makes audiences hard to feel the sense of presence. It's time to have systematic research to find a way out for the solution of traditional theatrical stage design. This study suggests the solutions for remediation of traditional theatrical stage design, so we are going to research with laying emphasis on the cooperative works between the fields of theatrical stage design and the Visual Effects par that forms extensive and diverse portions. The proposal for remediation of traditional theatrical stage design with practical use of Visual Effects will create economical higher value-added through the systematization of close and cooperative work between the fields of Visual Effects and theatrical stage design. In addition, the systematization of the cooperation of these two parts will make another communicative paradigm that audiences have never been able to experience before in traditional theatrical stage design.

• Composites Research
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• v.27 no.4
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• pp.123-129
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• 2014

Ceramic matrix composites (CMCs) consist of such reinforcements as carbides, nitrides, borides and oxides, which have high melting points, low density, high modulus and high strength, for the purpose of increasing toughness. These materials are used for heat shielding systems for aerospace vehicles, high-temperature gas turbine combustion chambers, turbine blades, stator vane parts, etc. Oxide CMCs are used for the components of burner and flame holder and the high-temperature gas duct. CMCs are also applied to brake disks, which are subjected to severe thermal shock, and slide bearing parts under heavy loads. The research and development of the CMC are progressed for the strategic purpose in defense and energy industry; for instance, for aerospace applications in the U.S., and for hyper-speed aircraft, gas turbines, and atomic fissions in U.S., Japan, and Europe.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.11
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• pp.46-56
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• 2010

The present research works investigated into the low velocity impact characteristics of DP 780 high strength steel sheet with 1.7 mm in thickness subjected to free boundary condition using three-dimensional finite element analysis. Finite element analysis was carried out via ABAQUS explicit code. Hyper-elastic model and the damping factor were introduced to improve an accuracy of the FE analysis. An appropriate FE model was obtained via the comparison of the results of the FE analyses and those of the impact tests. The influence of the impact energy and nose diameter of the impact head on the force-deflection curves, impact time, absorption characteristics of the impact energy, deformation behaviours, and stress-strain distributions was quantitatively examined using the results of FE analysis. The results of the FE analysis showed that the absorption rate of impact energy lies in the range of the 70.7-77.5 %. In addition, it was noted that the absorption rate of impact energy decreases when the impact energy increases and the nose diameter of the impact head decreases. The local deformation of the impacted region was rapidly increased when the impact energy was larger than 76.2 J and the nose diameter was 20 mm. A critical impact energy, which occur the instability of the DP780, was estimated using the relationship between the plastic strain and the impact energy. Finally, characteristics of the plastic energy dissipation and the strain energy density were discussed.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.12
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• pp.618-629
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• 2007

In this paper, we propose an effective memory test environment, called a virtualized kernel, for 64bit multi-core computing environments. The term of effectiveness means that we can test all of the physical memory space, even the memory space occupied by the kernel itself, without rebooting. To obtain this capability, our virtualized kernel provides four mechanisms. The first is direct accessing to physical memory both in kernel and user mode, which allows applying various test patterns to any place of physical memory. The second is making kernel virtualized so that we can run two or more kernel image at the different location of physical memory. The third is isolating memory space used by different instances of virtualized kernel. The final is kernel hibernation, which enables the context switch between kernels. We have implemented the proposed virtualized kernel by modifying the latest Linux kernel 2.6.18 running on Intel Xeon system that has two 64bit dual-core CPUs with hyper-threading technology and 2GB main memory. Experimental results have shown that the two instances of virtualized kernel run at the different location of physical memory and the kernel hibernation works well as we have designed. As the results, the every place of physical memory can be tested without rebooting.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.702-714
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• 2020

Stock investment is a personal investment technique that has gathered tremendous interest since the reduction in interest rates and tax exemption. However, it is risky especially for those who do not have expert knowledge on stock volatility. Therefore, it is well understood that accurate stock trend prediction can greatly help stock investment, giving birth to a volume of research work in the field. In order to compare different research works and to optimize hyper-parameters for prediction models, it is required to have an evaluation standard that can accurately assess performances of prediction models. However, little research has been done in the area, and conventionally used methods have been employed repeatedly without being rigorously validated. For this reason, we first analyze performance evaluation of stock trend prediction with respect to performance metrics and data composition, and propose a fair evaluation method based on prediction disparity ratio.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.557-561
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• 2014

In this work, Altair Engineering's vibroacoustic modeling approach is used to simulate the acoustic signature of a simplified automobile in a wind tunnel. The modeling approach relies on a two step procedure involving simulation and extraction of acoustic sources using a high fidelity Computational Fluid Dynamics (CFD) simulation followed by propagation of the acoustic energy within the structure and passenger compartment using a structural dynamics solver. The tools necessary to complete this process are contained within Altair's HyperWorks CAE software suite. The CFD simulations are performed using AcuSolve and the structural simulations are performed using OptiStruct. This vibroacoustics simulation methodology relies on calculation of the acoustic sources from the flow solution computed by AcuSolve. The sources are based on Lighthill's analogy and are sampled directly on the acoustic mesh. Once the acoustic sources have been computed, they are transformed into the frequency domain using a Fast Fourier Transform (FFT) with advanced sampling and are subsequently used in the structural acoustics model. Although this approach does require the CFD solver to have knowledge of the acoustic simulation domain a priori, it avoids modeling errors introduced by evaluation of the acoustic source terms using dissimilar meshes and numerical methods. The aforementioned modeling approach is demonstrated on the Hyundai Simplified Model (HSM) geometry in this work. This geometry contains flow features that are representative of the dominant noise sources in a typical automobile design; namely vortex shedding from the passenger compartment A-pillar and bluff body shedding from the side view mirrors. The geometry also contains a thick poroelastic material on the interior that acts to reduce the acoustic noise. This material is modeled using a Biot material formulation during the structural acoustic simulation. Successful prediction of the acoustic noise within the HSM geometry serves to validate the vibroacoustic modeling approach for automotive applications.

• Korean Journal of Acupuncture
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• v.25 no.3
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• pp.81-96
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• 2008

Objectives : The purpose of the present study is to determine the effective analgesic parameters of manual acupuncture (MA) and/or electroacupuncture (EA), thus how MA & EA of specific acupoint works after acute ankle sprain in rats. Thus, one series of experiments was designed to analyze the analgesic effects of acupuncture in either the normal or sprained rat, by comparing the behavioral features before and after MA or EA at several acupoints. Methods : Ankle sprain was induced manually by hyper-extension of ligaments of the right ankle in rat. Either MA or EA was applied to the LI4, TE17, 足三里 and SI-6 acupoints at an intensity of 2 mA (1 ms pulse duration) with a frequency of 10 Hz for 30 minutes. Results : Behaviorally, manual acupuncture or electroacupuncture produced potent analgesic effects on acute ankle sprained animals as measured by weight bearing capacity of the affected limb. Furthermore, antinociceptive effect of EA was suppressed by alpha adrenoceptor antagonist phentolamine (5 mg/kg, i.p.) but not by opioid antagonist naltrexone (10 mg/kg, i.p.). Conclusions : It is suggested that acupuncture-induced antinociception may involve the descending inhibition of ${\alpha}2$-adrenoceptor.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.27-33
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• 2021

The whole world now is dealing with Coronavirus, and it has turned to be one of the most widespread and long-lived pandemics of our times. Reports reveal that the infectious disease has taken toll of the almost 80% of the world's population. Amidst a lot of research going on with regards to the prediction on growth and transmission through Symptomatic carriers of the virus, it can't be ignored that pre-symptomatic and asymptomatic carriers also play a crucial role in spreading the reach of the virus. Classification Algorithm has been widely used to classify different types of COVID-19 carriers ranging from simple feature-based classification to Convolutional Neural Networks (CNNs). This research paper aims to present a novel technique using a Random Forest Machine learning algorithm with hyper-parameter tuning to classify different types COVID-19-carriers such that these carriers can be accurately characterized and hence dealt timely to contain the spread of the virus. The main idea for selecting Random Forest is that it works on the powerful concept of "the wisdom of crowd" which produces ensemble prediction. The results are quite convincing and the model records an accuracy score of 99.72 %. The results have been compared with the same dataset being subjected to K-Nearest Neighbour, logistic regression, support vector machine (SVM), and Decision Tree algorithms where the accuracy score has been recorded as 78.58%, 70.11%, 70.385,99% respectively, thus establishing the concreteness and suitability of our approach.