• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1003-1004
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• 2007

This paper deals with the PM performance evaluations in a variable flux memory motor (VFMM) using a coupled finite element method (FEM) and Preisach modeling, which is presented to analyze the magnetic characteristics of permanent magnets. The focus of this paper is the operation characteristics evaluation relative to magnetizing direction and quantity of permanent magnets on redemagnetization condition in a variable flux memory motor(VFMM).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.6
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• pp.938-948
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• 2001

In this paper, we present an exoskeletal haptic device named SKK Hand Master. This device is directly driven linkages actuated with small ultrasonic motors. By adopting ultrasonic motors that have advantageous features useful for cybernetic actuators, a compact haptic device containing whole driving packages can be established without additional power transmissions such as tendons. Methods for measuring joint postures and joint torques are developed and a new control strategy called PWM/PS is proposed to overcome intrinsic disadvantages such as hysteresis. Issues regarding design and construction of the device are addressed and several results of experiments for the evaluations of performance are included.

• International Journal of Contents
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• v.12 no.2
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• pp.37-41
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• 2016

In this paper, we propose a friend recommendation scheme that takes into consideration the attribute information of a POI and a user's movement patterns. The proposed scheme broadly consists of a part that filters out other users who have different preferences by calculating preferences using the attribute information of users and a part that finds a moving trajectory close to that of a user with a pattern-matching scheme. To verify the superiority of the proposed scheme, we compare it with existing schemes through various performance evaluations.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.584-589
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• 2008

A bi-modal tram has been developing to consist of articulated-two cars propelled by CNG hybrid (series type) in Korea since 2003. All wheels are driven by electrical motors independently, which can eliminate differential gears to reduce turning radius and make low floor to provide the old and the handicapped with easy access. In the bi-modal tram, therefore, reduction gear unit is key technology to make low floor and drive wheels independently. This study was aimed at performance evaluations of the reduction gear unit for the bi-modal tram. Oil leakage, oil temperature, vibration, acoustic noise in idle operations were measured for the reduction gear unit of the bimodal tram.

• Nuclear Engineering and Technology
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• v.35 no.2
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• pp.121-132
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• 2003

To reduce the construction cost and enhance the safety of sodium cooled liquid metal reactors, various kinds of new design concepts were evaluated using the KALIMER operation condition. The required equipment sizes were set for plant electricity output to be similar to that of KALIMER. The evaluations were made focusing on the plant performance and implementation practicality. Each design concept was evaluated for the concept itself and design impacts to interfacing systems. Through the evaluation of the concepts, it was found that the most favorable design concept is the integrated steam generator with forced convection using lead bismuth as the intermediate heat transfer fluid between the primary sodium tube and feed water/steam tube in the steam generator.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.317-319
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• 2022

Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.

• ETRI Journal
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• v.46 no.3
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• pp.513-525
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• 2024

Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.91-100
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• 2020

This paper presents an evaluation framework for prototyping multimedia streaming services including audio and video in a distributed and/or decentralized storage that can evaluate service quality and performance under various network conditions. The evaluation framework focuses on important indicators which measure and improve service quality by applying decentralized storage to multimedia streaming services that can mimic the scalability of the existing server-client software architecture and the issue of a single point of failure. The integrated framework not only measures performance indicators for evaluating the quality and performance of multimedia streaming on open source based multimedia content streaming services, but also adjusts network quality using network virtualization technology for comprehensive evaluations. The experimental results show that the integrated framework has low overhead in building and operating a decentralized storage with multimedia streaming services on a single host computer which validates the scalability of the developed framework.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.337-348
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• 2015

Touch input method is unintended difficulties regarding touch and input have increased with touch input methods when compared to using a mouse for input in previously existing menus. This study attempted to analyze usability evaluations according to form and size changes of minimal button forms in button menus. This attempted to verify possibilities through more effective applications of the quantitative performance prediction evaluation model through comparative analysis of Fitts' Law, the representative model of the regression model formula and the interface human performance evaluation method, so that applications can be made in interface designs of touch input methods. Therefore it was significant in that it made reflections on design with consideration given to use user times according to button forms and size changes that can be applied to touch screens.