• Title/Summary/Keyword: 수요패턴

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Design of IoT-based Energy Monitoring System for Residential Building (IoT 기반 주택형 건물 에너지 모니터링 시스템 설계)

  • Lee, Min-Goo;Jung, Kyung-Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1223-1230
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    • 2021
  • Recently, energy resource management is a major concern around the world. Energy management activities minimize environmental impacts of the energy production. This paper presents design and prototyping of a home electric energy monitoring system that provides residential consumers with real time information about their electricity use. The developed system is composed of an in-house sensing system and a server system. The in-home sensing system is a set of wireless smart plug which have an AC power socket, a relay to switch the socket ON/OFF, a CT sensor to sense current of load appliance and a Kmote. The Kmote is a wireless communication interface based on TinyOS. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to residential consumers. We analyzed and presented energy consumption data from electrical appliances for 3 months in home. The experimental results show the promising possibilities to estimate the energy consumption patterns and the current status.

AI based complex sensor application study for energy management in WTP (정수장에서의 에너지 관리를 위한 AI 기반 복합센서 적용 연구)

  • Hong, Sung-Taek;An, Sang-Byung;Kim, Kuk-Il;Sung, Min-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.322-323
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    • 2022
  • The most necessary thing for the optimal operation of a water purification plant is to accurately predict the pattern and amount of tap water used by consumers. The required amount of tap water should be delivered to the drain using a pump and stored, and the required flow rate should be supplied in a timely manner using the minimum amount of electrical energy. The short-term demand forecasting required from the point of view of energy optimization operation among water purification plant volume predictions has been made in consideration of seasons, major periods, and regional characteristics using time series analysis, regression analysis, and neural network algorithms. In this paper, we analyzed energy management methods through AI-based complex sensor applicability analysis such as LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Units), which are types of cyclic neural networks.

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Forecasting the Growth of Smartphone Market in Mongolia Using Bass Diffusion Model (Bass Diffusion 모델을 활용한 스마트폰 시장의 성장 규모 예측: 몽골 사례)

  • Anar Bataa;KwangSup Shin
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.193-212
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    • 2022
  • The Bass Diffusion Model is one of the most successful models in marketing research, and management science in general. Since its publication in 1969, it has guided marketing research on diffusion. This paper illustrates the usage of the Bass diffusion model, using mobile cellular subscription diffusion as a context. We fit the bass diffusion model to three large developed markets, South Korea, Japan, and China, and the emerging markets of Vietnam, Thailand, Kazakhstan, and Mongolia. We estimate the parameters of the bass diffusion model using the nonlinear least square method. The diffusion of mobile cellular subscriptions does follow an S-curve in every case. After acquiring m, p, and q parameters we use k-Means Cluster Analysis for grouping countries into three groups. By clustering countries, we suggest that diffusion rates and patterns are similar, where countries with emerging markets can follow in the footsteps of countries with developed markets. The purpose was to predict the timing and the magnitude of the market maturity and to determine whether the data follow the typical diffusion curve of innovations from the Bass model.

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.

The Economic Growth of Korea Since 1990 : Contributing Factors from Demand and Supply Sides (1990년대 이후 한국경제의 성장: 수요 및 공급 측 요인의 문제)

  • Hur, Seok-Kyun
    • KDI Journal of Economic Policy
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    • v.31 no.1
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    • pp.169-206
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    • 2009
  • This study stems from a question, "How should we understand the pattern of the Korean economy after the 1990s?" Among various analytic methods applicable, this study chooses a Structural Vector Autoregression (SVAR) with long-run restrictions, identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts. To that end, SVAR is applied to four economic models; Blanchard and Quah (1989)'s 2-variable model, its 3-variable extensions, and the two other New Keynesian type linear models modified from Stock and Watson (2002). Especially, the latter two models are devised to reflect the recent transitions in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting). When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea's economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea's high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of each sector on overall economic status. Despite the fact that a diverse mixture of models and impacts has been used for analysis, always two common findings are observed in the result. Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea's potential growth rate. The contents of this paper are constructed as follows: The second section observes the recent trend of the economic development of Korea and related Korean articles, which might help in clearly defining the scope and analytic methodology of this study. The third section provides an analysis model to be used in this study, which is Structural VAR as mentioned above. Variables used, estimation equations, and identification conditions of impacts are explained. The fourth section reports estimation results derived by the previously introduced model, and the fifth section concludes.

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Development of Intelligent Job Classification System based on Job Posting on Job Sites (구인구직사이트의 구인정보 기반 지능형 직무분류체계의 구축)

  • Lee, Jung Seung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.123-139
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    • 2019
  • The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

An Exploratory Study on the Status of and Demand for Higher Education Programs in Fashion in Myanmar (미얀마의 패션 고등교육 현황과 수요에 대한 탐색적 연구)

  • Kang, Min-Kyung;Jin, Byoungho Ellie;Cho, Ahra;Lee, Hyojeong;Lee, Jaeil;Lee, Yoon-Jung
    • Journal of Korean Home Economics Education Association
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    • v.34 no.3
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    • pp.1-23
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    • 2022
  • This study examined the perceptions of Myanmar university students and professors regarding the status and necessity of higher education programs in fashion. Data were collected from professors in textile engineering at Yangon Technological University and Myanmar university students. Closed- and open-ended questions were asked either through interviews or by email. The responses were analyzed using keyword extraction and categorization, and descriptive statistics(closed questions). Generally, the professors perceived higher education, as well as the cultural industries including art and fashion, as important for Myanmar's social and economic development. According to the students interests in pursuing a degree in textile were limited, despite the high interest in fashion. Low wages in the apparel industry and lack of fashion degrees that meet the demand of students were cited as reasons. The demand was high for educational programs in fashion product development, fashion design, pattern-making, fashion marketing, branding, management, costume history, and cultural studies. Students expected to find their future career in textiles and clothing factories. Many students wanted to be hired by global fashion brands for higher salaries and training for advanced knowledge and technical skills. They perceived advanced fashion education programs will have various positive effects on Myanmar's national economy.

A Spatial Statistical Method for Exploring Hotspots of House Price Volatility (부동산 가격변동 한스팟 탐색을 위한 공간통계기법)

  • Sohn, Hak-Gi;Park, Key-Ho
    • Journal of the Korean Geographical Society
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    • v.43 no.3
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    • pp.392-411
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    • 2008
  • The purpose of this paper is to develop a method for exploring hotspot patterns of house price volatility where there is a high fluctuation in price and homogeneity of direction of price volatility. These patterns are formed when the majority of householders in an area show an adaptive tendency in their decision making. This paper suggests a method that consists of two analytical parts. The first part uses spatial scan statistics to detect spatial clusters of houses with a positive range of price volatility. The second part utilizes local Moran's I to evaluate the homogeneity of direction of price volatility within each cluster. The method is applied to the areas of Gangnam-Gu, Seocho-Gu, and Songpa-Gu in Seoul from August to November of 2003; the Participatory Government of Korea designated these areas and this period as the most speculative. The results of the analysis show that the area around Gaepo-Dong was as a hotspot before the Government's anti-speculative 10.29 policy in 2003; the house prices in the same area stabilized in October, 2003 and the area was identified as a coldspot in December, 2003. This case study shows that the suggested method enables exploration of hotspot of house price volatility at micro spatial scales which had not been detected by visual analysis.

Policy and Strategy Implications of Smart Electricity Distribution Technologies in the Perspective of IT Ecosystem (스마트 배전의 경쟁전략 및 정책 시사점: IT Ecosystem의 관점에서)

  • Kim, Tae-Ha;Park, Chan-Hi
    • Information Systems Review
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    • v.12 no.1
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    • pp.189-207
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    • 2010
  • We applied IT ecosystem analysis to Smart Grid system in this paper and thereby compared various arguments about Smart Grid technologies against the reality of the power generation and distribution in South Korea with a special attention to the power distribution side. Our work attempts to propose policy implications in the government-level based on a firm-level analysis using the framework of the competitive strategy and advantage. The Smart Grid initiative is expected to enhance the efficiency in the power generation and distribution. In addition, the Smart Grid initiative aims at capturing the opportunities in the electric power business such as parts, components, supplies, and system products in the global arena. Prerequisites of smart distribution system include building infrastructure based on smart distribution parts, information systems, communication technologies, and developing various application programs and interfaces that would interact with the consumers. Consumers are expected to play an integral role by changing their consumption patterns in response to dynamic pricing and quality choices enabled by the smart distribution technologies. In order to induce the consumers to participate actively in the program, firms and policy makers should consider providing consumers economic incentives and proper education for better understanding of new technologies. Our work helps policy makers and firm better understand the nature of technology and stakeholders for the successful implementation of smart distribution technologies.

Evolution strategies of Digital Camera to cope with the progress of the Imaging Device and Web (이미징 디바이스 및 웹의 발전에 대응한 디지털 카메라의 진화전략에 관한 연구)

  • An, Ho-Seong;Byeon, Sang-Yeong;Kim, Jae-Beom
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2009.11a
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    • pp.79-82
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    • 2009
  • 본 연구는 인터넷의 진화 및 이미징 디바이스 전반의 발달에 따른 디지털 카메라의 진화 전략을 다룬 논문이다. 오늘날의 카메라 기술은 하루가 다르게 발전해 나가고 있다. 수동 필름 카메라에서부터 최첨단 하이브리드(hybrid) 카메라에 이르기 까지 카메라는 끊임없이 진화해 왔으며 사용자 계층 역시 다양해지고 있다. 디지털이 적용된 디지털 카메라의 경우, 웹의 발전과 더불어 활용도가 다양해 짐에 따라서 기존에는 전문가와 비전문가 계층으로 명확하게 나뉘던 사용자 계층도 그 경계가 모호해졌으며 사용자의 수 역시 비약적으로 증가하였다. 수많은 사업자들이 디지털 카메라 시장에 진출함에 따라, 높은 성장세가 지속되던 컴팩트 카메라 (compact camera)시장은 과포화기에 접어들어 성장성이 점차 감소하는 추세에 있으며, 전문가의 영역으로 여겨졌던 DSLR 시장 역시 선발업체의 높은 진입장벽과 이를 극복하기 위한 후발업체의 지속적인 도전으로 인해 경쟁은 치열하고 이익은 내기 어려운 레드 오션(red ocean)이 되었다. 이러한 상황 속에서 디지털 카메라가 활용될 수 있는 대표적 매체인 웹 역시 '웹 2.0' 이라는 용어가 생길 정도로 발전했다. 웹2.0시대가 본격화되어 서로 다른 사용자들이 자유롭게 컨텐츠를 공유하고 누구든지 쉽게 정보의 생산에 동참할 수 있게 됨으로써 기존의 웹에서 일어나지 않았던 다양한 변화들이 생겨나게 되었다. 본 연구에서는 변화의 특징들을 살펴보기 위해 웹 2.0 시대의 대표적인 컨텐츠 공유 커뮤니티로 자리매김한 야후(Yahoo)사(社) 플리커(Flickr)의 사례를 통해 디지털 카메라 사용자들의 디지털 카메라 사용패턴을 살펴보고 이를 통해 디지털 카메라의 진화를 설명하고자 한다. 인터넷이 발전하며 디지털 카메라와 관련 되어 나타난 대표적인 변화는 일반 소비자가 진화하는 점 이라고 볼 수 있다. 컨텐츠의 공유가 자유로운 웹 플랫폼의 등장, 카메라 기술이 결합된 소형 디지털 단말기의 발전 등으로 인해 비전문가 영역에 속해있던 일반 소비자 계층에 Flickr와 같은 웹 커뮤니티에서의 활동을 통해 준전문가 계층으로 진입하려는 욕구가 생기게 되었는데, 이렇게 형성된 욕구에 따라 디지털 카메라 시장 역시 새로운 수요를 만나게 되었다. 본 연구에서는 경쟁이 치열한 시장 상황 속에서 디지털 카메라의 향후 발전 방향을 알아보기 위해 우선 디지털 카메라 기능을 나누어 본 후, 이미징 디바이스 시장과 웹의 발전 형태에 대해 분석해보았다. 이어 본 연구에서는 분류된 디지털 카메라의 기능을 바탕으로 웹 2.0 시대에 시장을 주도할 수 있는 디지털 카메라의 변화방향에 대해서 알아보았다. 본 연구는 감성적 및 이성적 측면에서 디지털 카메라의 향후 전개방향을 살펴보았다는 점에서 이론적 실무적 함의를 가지는 논문이라고 사료된다.

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