• ETRI Journal
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• v.41 no.6
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• pp.838-849
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• 2019

We present a permanent magnet-based spherical wheel motor that can be used in omnidirectional mobility applications. The proposed motor consists of a ball-shaped rotor with a magnetic dipole and a hemispherical shell with circumferential air-core coils attached to the outer surface acting as a stator. Based on the rotational symmetry of the rotor poles and stator coils, we are able to model the rotor poles and stator coils as dipoles. A simple physical model constructed based on a torque model enables fast numerical simulations of motor dynamics. Based on these numerical simulations, we test various control schemes that enable constant-speed rotation along arbitrary axes with small rotational attitude error. Torque analysis reveals that the back electromotive force induced in the coils can be used to construct a control scheme that achieves the desired results. Numerical simulations of trajectories confirm that even without explicit methods for correcting the rotational attitude error, it is possible to drive the motor with a low attitude error (<5°) using the proposed control scheme.

• Structural Engineering and Mechanics
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• v.63 no.5
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• pp.639-646
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• 2017

According to the multi-index system of dam safety assessment and the standard of safety, a comprehensive evaluation model for dam safety based on a cloud model is established to determine the basic probability assignment of the Dempster-Shafer theory. The Dempster-Shafer theory is improved to solve the high conflict problems via fusion calculation. Compared with the traditional Dempster-Shafer theory, the application is more extensive and the result is more reasonable. The uncertainty model of dam safety multi-index comprehensive evaluation is applied according to the two theories above. The rationality and feasibility of the model are verified through application to the safety evaluation of a practical arch dam.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.535-548
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• 2022

Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.2
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• pp.203-211
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• 2020

Objective: Staphylococcus aureus (S. aureus) is one of the major microorganisms responsible for subclinical mastitis in dairy cattle. The present study was designed with the aim to explore the DNA methylation patterns using the Fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP) techniques in a S. aureus-infected mouse model. Methods: A total of 12 out-bred Institute of Cancer Research female mice ranging from 12 to 13 weeks-old were selected to construct a mastitis model. F-MSAP analysis was carried out to detect fluctuations of DNA methylation between control group and S. aureus mastitis group. Results: Visible changes were observed in white cell counts in milk, percentage of granulocytes, percentage of lymphocytes, CD⁴⁺/CD⁸⁺ ratio (CD⁴⁺/CD⁸⁺), and histopathology of mice pre- and post-challenge with S. aureus. These findings showed the suitability of the S. aureus-infected mouse model. A total of 369 fragments was amplified from udder tissue samples from the two groups (S. aureus-infected mastitis group and control group) using eight pairs of selective primers. Results indicated that the methylation level of mastitis mouse group was higher than that in the control group. In addition, NCK-associated protein 5 (Nckap5) and transposon MTD were identified to be differentially methylated through secondary polymerase chain reaction and sequencing in the mastitis group. These observations might play an important role in the development of S. aureus mastitis. Conclusion: Collectively, our study suggests that the methylation modification in Nckap5 and transposon MTD might be considered as epigenetic markers in resistance to S. aureus-infected mastitis and provided a new insight into S. aureus mastitis research in dairy industry and public health.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.460-474
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• 2023

A simple but accurate mathematical model is crucial for dynamic simulations and controller design of helical coil once-through steam generator (OTSG). This paper presents a three-region movable boundary dynamic model of the helical coil OTSG. Based on the secondary side fluid conditions, the OTSG is divided into subcooled region (two control volumes), two-phase region (two control volumes) and superheated region (three control volumes) with movable boiling boundaries between each region. The nonlinear dynamic model is derived based on mass, energy and momentum conservation equations. And the linear model is obtained by using the transfer function and state space transformation, which is a 37-order model of five input and three output. Validations are made under full-power steady-state condition and four transient conditions. Results show good agreements among the nonlinear model, linear model and the RELAP5 model, with acceptable errors. This model can be applied to dynamic simulations and controller design of helical coil OTSG with constant primary-side flow rate.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.3
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• pp.237-244
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• 2013

A continuous, explicit drain-current equation for short-channel double-gate (DG) MOSFETs has been derived based on the explicit surface potential equation. The model is physically derived from Poisson's equation in each region of operation and adopted in the unified regional approach. The proposed model has been verified with numerical solutions, physically scalable with channel length and gate/oxide materials as well as oxide/channel thicknesses.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.348-351
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• 2005

In this study, solute breakthrough curves through the unsaturated zone were predicted using artificial neural network (ANN) by numerical tests and laboratory experiments. In the numerical tests, applicability of ANN model to prediction of breakthrough curves was evaluated using synthetic data generated by HYDRUS-2D. An appropriate strategy of ANN application and input data form were recommended. The ANN model was validated by laboratory experiments comparing with HYDRUS-2D simulations. The results show that the ANN model can be an effective method for forecasting solute breakthrough curves through the unsaturated zone when hydraulic data are available.

• Water Engineering Research
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• v.1 no.4
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• pp.309-320
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• 2000

In this study, laboratory study of the behavior of wastewater discharged from the Boston ocean outfall was compared with the predictions of mathematical models. The dta sets cover broad ranges of discharge conditions and oceanic conditions, and are associated with a typical type of outfall discharges with multiport diffusers. The laboratory data sets were obtained in density stratified towing tanks. These data sets were used to evaluate four commonly used models: UM, UDKHDEN, RSB and CORMI$\times$2 for minimum dilution, the height to the top of the wastefield, and wastefield thickness. For minimum diluation and height to the top of the wastefield, UM and RSB predictions agree well with laboratory data. UDKHDEN overestimated the minimum dilution and height to the top of the wastefield while CORMI$\times$2 underestimated these values. All of the model predictions for the wastefield thickness were widely scattered. about the measured values. The hydraulic model study reproduced the major features observed in the laboratory. It also afforded considerable insight into the mechanics of mixing of multiport risers which could not have been obtained either from the laboratory test or the mathematical models.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.401-402
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• 2007

In this paper, we propose an automatic method to finding corresponding points. One 2D image can be changed 3D shape by 3D model. The main idea is using gabor wavelet values from 3D model. And Elastic Bunch Graph Matching algorithm is more stable in 3D model.