• Title/Summary/Keyword: future Internet

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Prediction of Veterans Care Demand and Supply System for Veterans

  • Tae Gyu Yu
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.193-198
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    • 2023
  • The rapid aging of the veterans has reached a level that cannot handle the demand for veterans care through the existing veterans care infrastructure. Therefore, it is urgent to improve the quality of the overall service of veterans due to the deterioration of the quality of nursing services for veterans with various underlying diseases compared to general patients and the long-term waiting for admission to the veterans care center. In this situation, about 640,000 people are admitted to veterans care institutions, but only about 5% of them can enter the veterans care center smoothly. As of June 2020, the number of people waiting to enter the veterans care center exceeds 1,000, including 520 at Suwon Veterans Nursing Home, 1 at Gwangju Veterans Nursing Home, 47 at Gimhae Veterans Nursing Home, 39 at Daegu Veterans Nursing Home, 86 at Namyangju Veterans Nursing Home.. Therefore, in order to predict those who want to enter the Veterans Nursing Home and wait for admission, and to find an important basis for resolving the long-term atmosphere, the ratio of future care providers is predicted in 2022-2050 and 2022-2024 to establish a cooperative system. As a result, 6,988 people in 2022, 6,797 people in 2023, and 6,606 people in 2024 can be admitted when 'preferred linkage', and 12,057 people in 2022 when 'expanded linkage'. It was found that 11,837 people in 2023 and 11,618 people in 2024 could be admitted. This was derived by estimating the percentage of people who wish to enter the Veterans Nursing Home when linking private nursing homes, and eventually "additional acceptance" of 22.5% in 2022, 20.9% in 2023, 19.4% in 2024, and 38.8% in 2023, 36.3% in 2023, and 34.1% in 2024 are most efficiently available.

An Empirical Study on the Comparison of LSTM and ARIMA Forecasts using Stock Closing Prices

  • Gui Yeol Ryu
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.18-30
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    • 2023
  • We compared empirically the forecast accuracies of the LSTM model, and the ARIMA model. ARIMA model used auto.arima function. Data used in the model is 100 days. We compared with the forecast results for 50 days. We collected the stock closing prices of the top 4 companies by market capitalization in Korea such as "Samsung Electronics", and "LG Energy", "SK Hynix", "Samsung Bio". The collection period is from June 17, 2022, to January 20, 2023. The paired t-test is used to compare the accuracy of forecasts by the two methods because conditions are same. The null hypothesis that the accuracy of the two methods for the four stock closing prices were the same were rejected at the significance level of 5%. Graphs and boxplots confirmed the results of the hypothesis tests. The accuracies of ARIMA are higher than those of LSTM for four cases. For closing stock price of Samsung Electronics, the mean difference of error between ARIMA and LSTM is -370.11, which is 0.618% of the average of the closing stock price. For closing stock price of LG Energy, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. For closing stock price of SK Hynix, the mean difference is -830.7269 which is 1.00% of the average of the closing stock price. For closing stock price of Samsung Bio, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. The auto.arima function was used to find the ARIMA model, but other methods are worth considering in future studies. And more efforts are needed to find parameters that provide an optimal model in LSTM.

ITU-R Study on Frequency Sharing for Mobile Satellite Services (ITU-R의 이동위성업무 주파수 공유 연구 현황)

  • B.J. Ku;D.S. Oh
    • Electronics and Telecommunications Trends
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    • v.38 no.1
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    • pp.55-64
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    • 2023
  • Recently, preparations for 6G have led to the increasing interest in integrated or hybrid communication networks considering low-orbit satellite communication networks with terrestrial mobile communication networks. In addition, the demand for frequency allocation for new mobile services from low-orbit small satellites to provide global internet of things (IoT) services is increasing. The operation of such satellites and terrestrial mobile communication networks may inevitably cause interference in adjacent bands and the same band frequency between satellites and terrestrial systems. Focusing on the results of the recent ITU-R WP4C meeting, this study introduces the current status of frequency sharing and interference issues between satellites and terrestrial systems, and frequency allocation issues for new mobile satellite operations. Coexistence and compatibility studies with terrestrial IMT in L band and 2.6 GHz band, operated by Inmassat and India, respectively, and a new frequency allocation study (WRC-23 AI 1.18) are carried out to reflect satellite IoT demand. For the L band, technical requirements have been developed for emission from IMT devices at 1,492 MHz to 1,518 MHz to bands above 1,518 MHz. Related studies in the 2 GHz and 2.6 GHz bands are not discussed due to lack of contributions at the recent meeting. In particular, concerning the WRC-23 agenda 1.18 study on the new frequency allocation method of narrowband mobile satellite work in the Region 1 candidate band 2,010 MHz to 2,025 MHz, Region 2 candidate bands 1,695 MHz to 1,710 MHz, 3,300 MHz to 3,315 MHz, and 3,385 MHz to 3,400 MHz, ITU-R results show no new frequency allocation to narrow mobile satellite services. Given the expected various collaborations between satellites and the terrestrial component are in the future, interference issues between terrestrial IMT and mobile satellite services are similarly expected to continuously increase. Therefore, participation in related studies at ITU-R WP4C and active response to protect terrestrial IMT are necessary to protect domestic radio resources and secure additional frequencies reflecting satellite service use plans.

Development of exothermic system based on internet of things for preventing damages in winter season and evaluation of applicability to railway vehicles

  • Kim, Heonyoung;Kang, Donghoon;Joo, Chulmin
    • Smart Structures and Systems
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    • v.29 no.5
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    • pp.653-660
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    • 2022
  • Gravel scattering that is generated during operation of high-speed railway vehicle is cause to damage of vehicle such as windows, axle protector and so on. Especially, those are frequently occurred in winter season when snow ice is generated easily. Above all, damage of vehicle windows has not only caused maintenance cost but also increased psychological anxiety of passengers. Various methods such as heating system using copper wire, heating jacket and heating air are applied to remove snow ice generated on the under-body of vehicle. However, the methods require much run-time and man power which can be low effectiveness of work. Therefore, this paper shows that large-area heating system was developed based on heating coat in order to fundamentally prevent snow ice damage on high-speed railway vehicle in the winter season. This system gives users high convenience because that can remotely control the heating system using IoT-based wireless communication. For evaluating the applicability to railroad sites, a field test on an actual high-speed railroad operation was conducted by applying these techniques to the brake cylinder of a high-speed railroad vehicle. From the results, it evaluated how input voltage and electric power per unit area of the heating specimen influences exothermic performance to draw the permit power condition for icing. In the future, if the system developed in the study is applied at the railroad site, it may be used as a technique for preventing all types of damages occurring due to snow ice in winter.

A Research on the Audio Utilization Method for Generating Movie Genre Metadata (영화 장르 메타데이터 생성을 위한 오디오 활용 방법에 대한 연구)

  • Yong, Sung-Jung;Park, Hyo-Gyeong;You, Yeon-Hwi;Moon, Il-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.284-286
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    • 2021
  • With the continuous development of the Internet and digital, platforms are emerging to store large amounts of media data and provide customized services to individuals through online. Companies that provide these services recommend movies that suit their personal tastes to promote media consumption. Each company is doing a lot of research on various algorithms to recommend media that users prefer. Movies are divided into genres such as action, melodrama, horror, and drama, and the film's audio (music, sound effect, voice) is an important production element that makes up the film. In this research, based on movie trailers, we extract audio for each genre, check the commonalities of audio for each genre, distinguish movie genres through supervised learning of artificial intelligence, and propose a utilization method for generating metadata in the future.

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By Analyzing the IoT Sensor Data of the Building, using Artificial Intelligence, Real-time Status Monitoring and Prediction System for buildings (건축물 IoT 센서 데이터를 분석하여 인공지능을 활용한 건축물 실시간 상태감시 및 예측 시스템)

  • Seo, Ji-min;Kim, Jung-jip;Gwon, Eun-hye;Jung, Heokyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.533-535
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    • 2021
  • The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

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Analyzing Intention to Use Shared E-scooters Considering Individual Travel Attitudes : The Case of Seoul Metropolitan Areas (개인 통행성향을 고려한 공유 전동킥보드 이용의향 분석: 서울시를 중심으로)

  • Lee, Yoonhee;Koo, Jahun;Choo, Sangho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.1-16
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    • 2022
  • Recently, e-scooters have been attracting attention as eco-friendly modes of transportation in cities due to an increasing interest in the environment. Accordingly, various studies on usage behavior are being conducted, but studies that reflect individual travel attitudes are insufficient. Therefore, this study surveyed commuters in Seoul and analyzed respondents' traveling attitudes through factor analysis. It also built a binary logistic regression model for the intention to use shared e-scooters to determine how individual travel behaviors are affected. In particular, the model results showed that age, the main mode of transportation (car), walking time to the bus stop, and four travel attitude variables (disutility of travel, preference to self-drive, internet/smartphone friendliness, and willingness to pay extra money for services) significantly affected the intention to use shared e-scooters. This study is expected to be used as basic data, with aspect to travel behavior, for the efficient operation and use of shared e-scooters in the future.

A Study on Expression Characteristics of Indoor Spaces and Food related Elements in Fusion Korean Restaurants (퓨전 한식 레스토랑에 나타난 실내공간과 음식관련요소의 표현특성에 관한 연구)

  • Lee, Ji-Hyun;Oh, Hye-Kyung
    • Journal of the Korean Society of Food Culture
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    • v.23 no.2
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    • pp.204-213
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    • 2008
  • In this age of information ruled by new technologies and knowledge, the world is interconnected as a single community, and within this trend of globalization, new cultural codes are emerging through temporal fusion between the past and the present and spatial fusion between different regions and countries. In this situation, it seems meaningful to review Korean fusion foods and restaurants serving such foods, as well as to consider their future directions. Thus, the objective of the present study was to survey and analyze Korean fusion restaurants representing Korean culture not only in Korea, but also in foreign cities, and to identify the expression characteristics of such restaurants. Based on restaurants recommended in relevant magazines and on Internet sites, 18 spaces were selected, visited, and surveyed, in which tradition and modernism were well-mixed. Data on the shapes, materials, colors, and patterns of spatial elements and food-related elements, including photographs, were collected and analyzed. The results are as follows. Of the 18 restaurants, 13 (72%) showed temporal fusion in both spatial and food-related elements, 4 showed temporal fusion in spatial elements and cultural fusion in food-related elements, and 1 showed cultural fusion in both spatial and food-related elements. In general, the spaces were mainly designed with modern elements and partially with traditional elements (ceilings, windows, furniture, articles), and the fusion of food-related elements was made in diverse forms that included temporal fusion restructuring traditional menus contemporarily, and cultural fusion harmonizing traditional food with Western cookery.

Current State of Animation Industry and Technology Trends - Focusing on Artificial Intelligence and Real-Time Rendering (애니메이션 산업 현황과 기술 동향 - 인공지능과 실시간 렌더링 중심으로)

  • Jibong Jeon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.821-830
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    • 2023
  • The advancement of Internet network technology has triggered the emergence of new OTT video content platforms, increasing demand for content and altering consumption patterns. This trend is bringing positive changes to the South Korean animation industry, where diverse and high-quality animation content is becoming increasingly important. As investment in technology grows, video production technology continues to advance. Specifically, 3D animation and VFX production technologies are enabling effects that were previously unthinkable, offering detailed and realistic graphics. The Fourth Industrial Revolution is providing new opportunities for this technological growth. The rise of Artificial Intelligence (AI) is automating repetitive tasks, thereby enhancing production efficiency and enabling innovations that go beyond traditional production methods. Cutting-edge technologies like 3D animation and VFX are being continually researched and are expected to be more actively integrated into the production process. Digital technology is also expanding the creative horizons for artists. The future of AI and advanced technologies holds boundless potential, and there is growing anticipation for how these will elevate the video content industry to new heights.

Achieving Relative Loss Differentiation using D-VQSDDP with Differential Drop Probability (차별적이니 드랍-확률을 갖는 동적-VQSDDP를 이용한 상대적 손실차별화의 달성)

  • Kyung-Rae Cho;Ja-Whan Koo;Jin-Wook Chung
    • Annual Conference of KIPS
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    • 2008.11a
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    • pp.1332-1335
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    • 2008
  • In order to various service types of real time and non-real time traffic with varying requirements are transmitted over the IEEE 802.16 standard is expected to provide quality of service(QoS) researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the Multiple-RED(Random Early Detection) model, to get the performance of the best suited, we analyzes its main control parameters (maxth, minth, maxp) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-VQSDDP(Variable Queue State Differential Drop Probability)T, is proposed to overcome M-RED's shortcoming as well as supports static maxp parameter setting values for relative and each class proportional loss differentiation. M-RED is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore maxp parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-VQSDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.