• Journal of Information Technology Services
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• v.15 no.4
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• pp.1-24
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• 2016

With the innovation of information technology, non-face-to-face robo advisor with high accessibility and convenience is spreading. The current robot advisor recommends appropriate investment products after understanding the investment propensity based on the structured data entered directly or indirectly by individuals. However, it is an inconvenient and obtrusive way for financial consumers to inquire or input their own subjective propensity to invest. Hence, this study proposes a way to deduce the propensity to invest in unstructured data that customers voluntarily exposed during consultation or online. Since prediction performance based on unstructured document differs according to the characteristics of text, in this study, classification algorithm optimized for the characteristic of text left by financial consumers is selected by performing prediction performance evaluation of various learning discrimination algorithms and proposed an intelligent method that automatically recommends investment products. User tests were given to MBA students. After showing the recommended investment and list of investment products, satisfaction was asked. Financial consumers' satisfaction was measured by dividing them into investment propensity and recommendation goods. The results suggest that the users high satisfaction with investment products recommended by the method proposed in this paper. The results showed that it can be applies to non-face-to-face robo advisor.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.933-938
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• 2006

Different multimedia services over networks not only require different amounts of bandwidth but also have different Qualify of Service (QoS) requirements. For example, QoS guarantees for higher priority calls is an important issue in multimedia communication networks. In this paper, we develop an adaptive bandwidth management algorithm, which is able to provide QoS guarantees for higher priority calls while accommodating as many heterogeneous multimedia call connections as possible. Our scheme, based on reservation and bandwidth adaptation, manages bandwidth based on real time estimates of current network conditions. Simulation results indicate the superior performance of our scheme providing excellent trade off between contradictory requirements.

• Journal of Power Electronics
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• v.15 no.2
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• pp.469-478
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• 2015

In order to promote the application of switched reluctance machines (SRM) in electric vehicles (EVs), the braking torque closed-loop control of a SRM is proposed. A hysteresis current regulator with the soft chopping mode is employed to reduce the switching frequency and switching loss. A torque estimator is designed to estimate the braking torque online and to achieve braking torque feedback. A feed-forward plus saturation compensation torque regulator is designed to decrease the dynamic response time and to improve the steady-state accuracy of the braking torque. The turn-on and turn-off angles are optimized by a genetic algorithm (GA) to reduce the braking torque ripple and to improve the braking energy feedback efficiency. Finally, a simulation model and an experimental platform are built. The simulation and experimental results demonstrate the correctness of the proposed control strategy.

• Journal of Power Electronics
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• v.15 no.2
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• pp.411-418
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• 2015

In this paper, a new method for the online estimation of equivalent series resistances (ESR) of the DC-link capacitors in induction machine (IM) drive systems with a front-end diode rectifier is proposed, where the ESR estimation is conducted during the regenerative operating mode of the induction machine. In the first place, a regulated AC current component is injected into the q-axis current component of the induction machine, which induces the current and voltage ripple components in the DC-link. By processing these AC signals through digital filters, the ESR can be estimated by a recursive least squares (RLS) algorithm. To acquire the AC voltage across the ESR, the DC-link voltage needs to be measured at a double sampling frequency. In addition, the ESR current is simply reconstructed from the stator currents and switching states of the inverter. Experimental results have shown that the estimation error of the ESR is about 1.2%, which is quite acceptable for condition monitoring of the capacitor.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.15-24
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• 2013

In recent years, the number of social network system has grown rapidly. Among them, social bookmarking system(SBS) is one of the most popular systems. SBS provides network platform which users can share and manage various types of online resources by using tags. In SBS, it can be possible to reflect tag and time in order to enhance the quality of personalized recommendation. In this paper, we proposed recommender system which reflect tag and time at weight generation and similarity calculation. Also we adapted proposed method to real dataset and the result of experiment showed that the our method offers better performance when such information is integrated.

• International Journal of Contents
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• v.17 no.4
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• pp.101-118
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• 2021

The prevalence of We-Media short videos has attracted emerging independent fashion designers (EIFD), a new force in the fashion industry directing their brand promotion to We-Media for amassing online followers. However, compared to famous content generators, EIFDs' creative, design-based visual appeal has not provided them with the significant edge. The former's success is admittedly supported by the platform backstage algorithm. Yet, the content is the cornerstone for building relationship between the sender and the reception. The authentic perception of the content is one of the basic appeals for which the audience chooses to follow the source. Therefore, with the EIFD short video as the research content, this study is established from the audience's perspective to understand the different dimensions of their authentic perceptions of EIFDs short video. The study was conducted mainly in the form of the Q method. The collection of 52 Q samples were realized through the Focus Group Interview and literature review on multidimensional authenticity. Thirty-six subjects participated in the sorting of the Q-sets. Finally, four dimensions of audience authenticity perceptions of EIFDs were derived: 'ingenuity', 'relevant', 'transparent', and 'experiential'. The corresponding short video content design strategies are suggested for effective communication of EIFDs and their personal brands.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.193-199
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• 2018

The commonly used delivery system for online merchandise has potential problems, not only missing but also criminal case. Also, the contemporary Kiosk type approach for delivery system has some problems in an initial installation cost, expense of management system and especially security weaknesses in the wireless communication. To resolve these issues, this paper is proposing a securely unmaned smart locker system that can handle up to 64 parcels. This is easily controlled and monitored by a smartphone. In addition to the system, an algorithm is proposed to make the security of wireless communications better. Finally, a method is proposed to minimize the cost of delivery by using centralized server.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.97-99
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• 2014

This study aims to suggest development model for ICT Teaching and Learning System adopting collective intelligence. First, we defined program modules according to functions which multimedia online encyclopedia-type e-textbook should have. Then, we also specified content information creating rules and procedures and content information searching methods. Finally, we developed the prototype which suggests user interface to collect and search information adopting information visualizing techniques. This study has significance in suggesting advanced form of ICT system in which qualified teachers can create, accumulate, and share information and students can explore information and expand search in self-directed manner.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.61-67
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• 2021

The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2414-2433
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• 2021

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.