• Title/Summary/Keyword: Power network

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Speech extraction based on AuxIVA with weighted source variance and noise dependence for robust speech recognition (강인 음성 인식을 위한 가중화된 음원 분산 및 잡음 의존성을 활용한 보조함수 독립 벡터 분석 기반 음성 추출)

  • Shin, Ui-Hyeop;Park, Hyung-Min
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.3
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    • pp.326-334
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    • 2022
  • In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

A Study on Deep Learning based Aerial Vehicle Classification for Armament Selection (무장 선택을 위한 딥러닝 기반의 비행체 식별 기법 연구)

  • Eunyoung, Cha;Jeongchang, Kim
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.936-939
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    • 2022
  • As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

A Study on "On-tact" Christian Education in the Post-Corona Era (포스트 코로나 시대의 "온택트(ontack)" 기독교교육에 관한 연구)

  • Yang, Kum Hee
    • Journal of Christian Education in Korea
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    • v.68
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    • pp.41-76
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    • 2021
  • This paper begins with the question of whether "on-tact" Christian education, which has become the most new-normal phenomenon since Corona 19, will remain as a decisive form of Christian education even in the post-Corona era. In order to answer that question, this study explored whether on-tact Christian education has its own domain of experience and educational elements that cannot be replaced by face-to-face education, specifically focusing on "types of on-tact Christian Education", "discussion of digital church" and "digital epistemology". Through research on "types of onn-tact Christian education," it confirmed that, when viewed on the basis of 'participation' or 'communication', on-tact Christian education has an independent field of experience and educational elements. Through contemplation on "digital ecclesiology", it found that on-tact education is the decisive channel for Christian education to reach digital generation. It also found a new metaphor from the "network" concept for the public church and the Kingdom of God. This paper also found that we experience the perception of the body that is expanded through the combination between the body and technology in the digital world, and that this is a unique epistemology that occurs only in the digital world. Based on the above points, it affirmed that on-tact Christian education is not simply a means of supplementing face-to-face education in the era of COVID-19, but is a Christian education that has an independent field of experience and educational power that face-to-face education cannot replace. Thus it foresees that on-tact Christian education will continue to expand as a center and form of Christian education even in the post-corona era.

An Exploratory Case Study of a Successful Online Start-up Fashion Shopping Store: Focusing on the Entrepreneurial Process of a Soho Shopping Mall (온라인 패션쇼핑몰의 성공적 창업에 대한 탐색적 사례연구: 소호쇼핑몰의 기업가적 과정을 중심으로)

  • Son, Mi Young
    • Science of Emotion and Sensibility
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    • v.25 no.3
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    • pp.91-106
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    • 2022
  • This study targets four Soho fashion shopping malls that are operating successfully in the online fashion market. This study analyzed the entrepreneurship process by dividing it into three stages. The results of the case study are as follows. In the case of Company S, the founder, who had little work experience, started an e-commerce business with a sense of fashion and entrepreneurship. It is a contemporary, casual brand with competitive prices, design power, and diverse product assortment, and the business performance was achieved through data management and analysis and the diversification of distribution channels. In the case of Company B, the founder, who had little work experience, started a manufacturing and e-commerce business by leveraging their SNS network capabilities and entrepreneurial spirit. It is a contemporary fashion brand with product competitiveness of specific items and start-up characteristics, and performance was achieved through the establishment of brand identity and market expansion. Third, Company M and Company C are examples of Soho fashion shopping malls where the founders with more extensive work experience at the time of founding their respective start-ups focused on brand recognition as their core competitiveness. In the case of Company M, the apparel brand was launched with a wealth of experience and design spirit. It is a fashion designer brand that stands out for its sensibility, and the owner has achieved performance through various entrepreneurial activities that broaden the corporate horizon. Company C is a manufacturing and e-commerce brand that was started with design capabilities and an entrepreneurial spirit. It is a luxury fashion brand that focuses on emotional expression, and the outcomes, such as brand recognition and sales, were achieved through active customer management. The results of this study can be used as basic data in education for and research of Soho shopping malls and the prospective founders.

Apartment Price Prediction Using Deep Learning and Machine Learning (딥러닝과 머신러닝을 이용한 아파트 실거래가 예측)

  • Hakhyun Kim;Hwankyu Yoo;Hayoung Oh
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.2
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    • pp.59-76
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    • 2023
  • Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

Design and Implementation of Economical Smart Wall Switch with IEEE 802.11b/g/n

  • Myeong-Chul Park;Hyoun-Chul Choi;Cha-Hun Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.103-109
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    • 2023
  • In this paper, we propose a smart wall switch based on IEEE 802.11b/g/n standard 2.4GHz band communication. As the 4th industrial era evolves, smart home solution development is actively underway, and application cases for smart wall switches are increasing. Most of the Chinese products that preoccupy the market through price competitiveness use Bluetooth and Zigbee communication switches. However, while ZigBee communication is low power, communication speed is slower than Bluetooth and network configuration through a separate hub is additionally required. The Bluetooth method has problems in that the communication range and speed are lower than Wi-Fi communication, the communication standby time is relatively long, and security is weak. In this study, an IEEE 802.11b/g/n smart wall switch applied with Wi-Fi communication technology was developed. In addition, through the two-wire structure, it is designed so that no additional cost is incurred through the construction of a separate neutral line in the building. The result of the study is more than 30% cheaper than the existing wall switch, so it is judged that it will be able to preoccupy the market not only in terms of technological competitiveness but also price competitiveness.

A Study on the Architecture for Avionics System of Jet Fighters (제트 전투기의 항공전자 시스템 아키텍처에 관한 연구)

  • Gook, Kwon Byeong;Won, Son Il
    • Journal of Aerospace System Engineering
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    • v.16 no.1
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    • pp.86-96
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    • 2022
  • The development trend of jet fighter's avionics system architecture is the digitization of subsystem component functions, increased RF sensor sharing, fiber optic channel networks, and modularized integrated structures. The avionics system architecture of the fifth generation jet fighters (F-22, F-35) has evolved into an integrated modular avionics system based on computing function integration and RF integrated sensor systems. The integrated modular avionics system of jet fighters should provide improved combat power, fault tolerance, and ease of jet fighter control. To this aim, this paper presents the direction and requirements of the next-generation jet fighter's avionics system architecture through analysis of the fifth generation jet fighter's avionics system architecture. The core challenge of the integrated modularized avionic system architecture requirements for next-generation fighters is to build a platform that integrates major components and sensors into aircraft. In other words, the architecture of the next-generation fighters is standardization of systems, sensor integration of each subsystem through open interfaces, integration of functional elements, network integration, and integration of pilots and fighters to improve their ability to respond and control.

Transmission of Korean Traditional Music - Focusing of Solo Instrumental Music for the Gayageum (12-stringed Zither) - (한국 전통음악의 전승과 미래 - 가야금산조를 중심으로 -)

  • Lee, Yong-Shik
    • (The) Research of the performance art and culture
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    • no.19
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    • pp.281-315
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    • 2009
  • Korean traditional music has been a process art which has been changed and re-created by musicians to mirror the musical aesthetics of contemporary people. Form court music, which has tried to keep the "authentic" form as much as possible, to folk music, which is closely associated to the people's life style, traditional music has expressed the life of the Korean people. From the early 20th century, traditional music faced a totally new music culture due to the Japanese annexation and rapid westernization. A new music network was established by modern theater and broadcast system. Many gayageum (12-stringed zither) masters were able to develop their own music in this new music culture. Female musicians came to exist because of a new music education system, called gwonbeon (school for female entertainers). Due to the rapid westernization, traditional music was becoming 'extinct'. The government's new system of Intangible Cultural Heritage tried to preserve traditional culture. Traditional music came to revive but became fossilized in order to preserve the 'archetype'. The so-called Living Human Treasures took power and became a social problem. The modern school education system was one of major factors for promotion of traditional music. However, it became one of main reasons for musicians to lose their musical creativity. Today, many performers and composers try to make a new composition and renovated musical instruments to suit the contemporary musical aesthetics.

A Study on the Economic Effects of Big Tech Companies: Focusing on the Google Revenue and Tax Issues (글로벌 플랫폼이 국내 경제에 미치는 영향 연구: 구글 매출 추정 및 세원잠식 사례연구를 중심으로)

  • Kang, Hyoung-Goo;Jeon, Seongmin
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.1
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    • pp.1-11
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    • 2023
  • Big tech companies are further strengthening its status against the background of data accumulation, price competitiveness by the platform, and competitive advantage due to the network effect. The competition subcommittee of the European Union(EU) imposed a huge fine on Google for antitrust violations, which was interpreted as an attempt to collect Google's unpaid taxes. In fact, taxation efforts in the form of 'Google tax' are underway, targeting expedient tax avoidance by global platforms. It has power and has a considerable influence on the startup ecosystem. The domestic sales and tax scale of global platforms, which have a great impact on domestic content startups and small and medium-sized venture companies, are not accurately measured. In the case of Google, according to research literature, sales in Korea were estimated at about 2 trillion to 3 trillion won in 2017, but Google Korea reported sales of 290 billion won in 2021 and paid 13 billion won in taxes. This study aims to verify the economic effect of the global platform that has a great influence on Korea, and specifically to quantitatively estimate the annual domestic sales and taxes of Google, a representative global platform. As a result of estimating Google's annual domestic sales and taxes based on the figures presented in the document related to Google's economic effect published by Google, the result was 4 to 9 trillion won in annual sales and 390.6 to 913.1 billion won in taxes. This study is meaningful in that it provides basic data on the direction of national and tax policies in the future digital economy era by estimating the problem of tax authority by country of global platform companies with a specific example of Google.

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Performance of Passive UHF RFID System in Impulsive Noise Channel Based on Statistical Modeling (통계적 모델링 기반의 임펄스 잡음 채널에서 수동형 UHF RFID 시스템의 성능)

  • Jae-sung Roh
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.835-840
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    • 2023
  • RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.