• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.40-49
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• 2010

A rule weight -based fuzzy classification model is proposed to analyze the patterns of admission-discharge of patients as a previous research for differential diagnosis of dyspnea. The proposed model is automatically generated from a labeled data set, supervised learning strategy, using three procedure methodology: i) select fuzzy partition regions from spatial distribution of data; ii) generate fuzzy membership functions from the selected partition regions; and iii) extract a set of candidate rules and resolve a conflict problem among the candidate rules. The effectiveness of the proposed fuzzy classification model was demonstrated by comparing the experimental results for the dyspnea patients' data set with 11 features selected from 55 features by clinicians with those obtained using the conventional classification methods, such as standard fuzzy classifier without rule weights, C4.5, QDA, kNN, and SVMs.

• Macromolecular Research
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• v.10 no.5
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• pp.266-272
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• 2002

Although the reptational model of Doi and Edwards gives a successful description of viscoelasticity of flexible linear polymers, the success is restricted to the terminal region./sup 1/ There have been several attempts to modify the Doi-Edwards model to describe wider range of time or frequency./sup 2-6/ This paper suggests a simple phenomenological model which can describe wider range of molecular weight than such molecular models can. Although our model is a phenomenological one, it is practical and convenient to predict the effect of molecular weight distribution on linear viscoelastic data because of its simple mathematical form.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.70-78
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• 2021

Naval surface ships and submarines could be exposed to non-contact underwater explosion(UNDEX) environment. Equipment installed on the ships and submarines could be damaged by shock load generated by UNDEX environment. Therefore, shock survivability of equipment generally evaluated by shock tests. Ground based shock test machine such as Light weight shock test machine(LVSM) is developed to simulate shock load caused by UNDEX environment. In this study, linear dynamic model of LVSM is proposed and evaluated to improve shock test design procedure. Parameters of the model are decided by optimizing time domain response compared to zero payload experiment. Proposed model is verified by comparing simulation results and test results of maximum payload experiment. Finally, shock test design using the model is described for various test equipment weight.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.352-358
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• 2022

Text mining is an important process used for analyzing the data collected from different sources like videos, audio, social media, and so on. The tools like Natural Language Processing (NLP) are mostly used in real-time applications. In the earlier research, text mining approaches were implemented using long-short memory (LSTM) networks. In this paper, text mining is performed using average-stochastic gradient descent weight-dropped (AWD)-LSTM techniques to obtain better accuracy and performance. The proposed model is effectively demonstrated by considering the internet movie database (IMDB) reviews. To implement the proposed model Python language was used due to easy adaptability and flexibility while dealing with massive data sets/databases. From the results, it is seen that the proposed LSTM plus weight dropped plus embedding model demonstrated an accuracy of 88.36% as compared to the previous models of AWD LSTM as 85.64. This result proved to be far better when compared with the results obtained by just LSTM model (with 85.16%) accuracy. Finally, the loss function proved to decrease from 0.341 to 0.299 using the proposed model

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3507-3522
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• 2022

Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.1
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• pp.32-40
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• 2018

In this research, a method of deriving statistical weight prediction formula which is used during the conceptual design phase was studied and it was programmed using Microsoft Excel and verified by applying to jet transport aircraft. The database was built while referencing the variables of conventional wing weight estimation formulas and it was used for modeling the jet transport wing weight regression equation. The model was evaluated using the K-fold cross validation method to solve the overfitting problem of the model.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1934-1944
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• 2017

As a key component of high-voltage power conversion system for electric vehicles (EVs), bidirectional DC/DC (Bi-DC/DC) is required to have high efficiency and light weight. Conventional design methods optimize the Bi-DC/DC at the maximum power dissipation point (MPDP). For EVs application, the work condition of the Bi-DC/DC is not strict as the MPDP, where the design method using MPDP may not be optimal during travel of EVs. This paper optimizes the Bi-DC/DC converter targeting efficiency and weight based on the driving cycle. By analyzing the two-phase interleaved Bi-DC/DC for hybrid energy storage systems (HESS) of EVs, its power dissipation is calculated, and an efficiency model is derived. On this basis, weight models of capacitor, inductor and heat sink are built, as well as a dynamic temperature model of heat sink. Based on these models, a method using New European Driving Cycle (NEDC) for optimal design of Bi-DC/DC which simultaneously considered efficiency and weight is proposed. The simulation result shows that compare with conventional optimization methods revealed that the optimization approach based on driving cycle allowed significant weight reduction while meeting the efficiency requirements.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.363-369
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• 2000

Due to environmental problem for reduction in fuel consumption, vehicle emission and etc., many automotive makers are trying to reduce the weight of the vehicle. The most effective way to reduce the weight of vehicle is to use lighter materials, aluminum, plastics. Aluminum Space Frame has many advantages in weight reduction, body stiffness, ease of model change and so on. So, most of automotive manufacturers are attempting to develope Aluminum Space Frame body. For these reasons, we have developed Aluminum Intensive Vehicle based on steel monocoque body with Hyundai Motor Company. We achieved about 30% weight reduction, the stiffness of our model was higher than that of conventional steel monocoque body. In this paper, with optimization using FEM analysis, we could get more weight reduction and body stiffness increase. In the long run, we analyzed by means of simulation using PAM-CRASH to evaluate crush and crash characteristic of Aluminum Intensive Vehicle in comparison to steel monocoque automotive.

• Journal of Preventive Medicine and Public Health
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• v.52 no.4
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• pp.234-241
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• 2019

Objectives: To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status. Methods: This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status. Results: Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight. Conclusions: These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.

• Tribology and Lubricants
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• v.40 no.1
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• pp.24-27
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• 2024

A monotype valve body for a dual clutch transmission has the potential to reduce costs, weight, and manufacturing time by modularizing various parts, including those of existing solenoid packs and valve bodies, into one through the application of super-precision die casting technology. However, this approach may lead to challenges such as reduced rigidity and increased interference due to modularization and compactness, impacting both product performance due to the reduced weight as well as durability and reliability. Unlike existing products, this approach requires a high-precision thin-wall block to avoid more complicated flow line formation, interference between flow lines, and leaks, as well as a strict quality requirement standard and precise inspections including detection of internal defects. To conduct precise inspections, we built an equivalent model corresponding to a driving distance of 300,000 km. Testing involved simulating actual road loads using a real vehicle and a chassis dynamometer in the FTP-75 mode (EPA Federal Test Procedure). The aim of the study was to establish a vehicle load-based part durability model for manufacturing a mono-type valve body and to develop fundamental technology for part weight reduction through preliminary design by introducing analytical weight reduction technology based on the derived results.