• 전자통신동향분석
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• 제36권1호
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• pp.99-108
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• 2021

Digital twins are digital replicas of objects and systems in the real world. These digital replicas in a virtual environment can be connected with smart sensors and a variety of analyses, and simulations of real-time data from these sensors enable effective the operation, rapid feedback, and future predictions of real world phenomena. Until now, digital twins have been adopted and used mainly in the field of manufacturing, especially for smart factories. As digital twins are expected to be useful not only for productivity improvement but also for social problem solving, it is predicted that they will be extended to other fields such as those of transportation and cities. Digital twins will especially help realize smart cities through real-time monitoring, operation, and predictions using virtual digital twin cities. This paper summarizes the trends in digital twins for smart cities, the concept of digital twins, their application to smart cities, the strategies of various countries, and the development status of companies.

• 전자통신동향분석
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• 제39권3호
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• pp.69-78
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• 2024

Cloud computing technology based on centralized high-performance computing has brought about major changes across the information technology industry and led to new paradigms. However, with the rapid development of the industry and increasing need for mass generation and real-time processing of data across various fields, centralized cloud computing is lagging behind the demand. This is particularly critical in emerging technologies such as autonomous driving, the metaverse, and augmented/virtual reality that require the provision of services with ultralow latency for real-time performance. To address existing limitations, distributed and edge cloud computing technologies have recently gained attention. These technologies allow for data to be processed and analyzed closer to their point of generation, substantially reducing the response times and optimizing the network bandwidth usage. We describe distributed and edge cloud computing technologies and explore the latest trends in their standardization.

• 전자통신동향분석
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• 제36권4호
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• pp.145-153
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• 2021

Data imputation is a crucial issue in data analysis because quality data are highly correlated with the performance of AI models. Particularly, it is difficult to collect quality time-series data for uncertain situations (for example, electricity blackout, delays for network conditions). Thus, it is necessary to research effective methods of time-series data imputation. Many studies on time-series data imputation can be divided into 5 parts, including statistical based, matrix-based, regression-based, deep learning (RNN and GAN) based methodologies. This study reviews and organizes these methodologies. Recently, deep learning-based imputation methods are developed and show excellent performance. However, it is associated to some computational problems that make it difficult to use in real-time system. Thus, the direction of future work is to develop low computational but high-performance imputation methods for application in the real field.

• 전자통신동향분석
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• 제36권6호
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• pp.13-24
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• 2021

Industrial networks has been developing various technologies from fieldbus technology to industrial Ethernet and time-sensitive networking. The industry expects that the 5G mobile network will solve the diverse and highly specific industrial site requirements. Accordingly, 3GPP has been developing standard functions to provide ultra-high reliability, ultra-high speed, ultra-connection, and ultra-low latency services, and 3GPP Rel-16 began developing ultra-low latency and ultra-high reliability communication functions for 5G mobile networks to support vertical industries. In this paper, we show the related standardization trends and requirements to apply industrial IoT service scenarios to 5G mobile networks, and in particular, we introduce 5G system features and extended 5G system architecture to provide time sensitive communication and time synchronization services.

• 한국실내디자인학회논문집
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• 제21권3호
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• pp.76-86
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• 2012

21st century has different characters from 20th century which was an era of machine and rationality based on the industrial revolution. With the advent of the digital revolution, it became an era of pluralism, culture, and emotion. The digital technology made it possible to connect the whole world together in real time and brought about the entirely new notion of time and space. It also dramatically altered the world view. Now we have a different set of social and cultural values from the past. This paper researched the influences of these social and cultural changes on public designs. The leading trends of public designs were analyzed and the successful cases were studied. The main research methodologies were the document review and the instrumental case study. The major social & cultural paradigms of a present era were classified as 'pluralism', 'digital & information revolution', 'human-centered value (against machine-centered value of 20th century)', and 'organic world view'. Each of the classified paradigms was analyzed more to find out the influences on the various trends of public designs. 'Pluralism' has influence on 'experiential public design', 'community art', and 'public design of local values'. 'Digital & information revolution' has influence on 'content-centered public design', 'smart public design', 'immaterial public design', and 'performance in public design'. 'Human-centered value' has influence on 'universal design approach in public design', and 'emotional public design'. 'Organic world view' has influence on 'sustainable public design', and 'ecological public design'.

• Healthcare Informatics Research
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• 제24권4호
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• pp.300-308
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• 2018

Objectives: Prompt detection is a cornerstone in the control and prevention of infectious diseases. The Integrated Disease Surveillance Project of India identifies outbreaks, but it does not exactly predict outbreaks. This study was conducted to assess temporal correlation between Google Trends and Integrated Disease Surveillance Programme (IDSP) data and to determine the feasibility of using Google Trends for the prediction of outbreaks or epidemics. Methods: The Google search queries related to malaria, dengue fever, chikungunya, and enteric fever for Chandigarh union territory and Haryana state of India in 2016 were extracted and compared with presumptive form data of the IDSP. Spearman correlation and scatter plots were used to depict the statistical relationship between the two datasets. Time trend plots were constructed to assess the correlation between Google search trends and disease notification under the IDSP. Results: Temporal correlation was observed between the IDSP reporting and Google search trends. Time series analysis of the Google Trends showed strong correlation with the IDSP data with a lag of -2 to -3 weeks for chikungunya and dengue fever in Chandigarh (r > 0.80) and Haryana (r > 0.70). Malaria and enteric fever showed a lag period of -2 to -3 weeks with moderate correlation. Conclusions: Similar results were obtained when applying the results of previous studies to specific diseases, and it is considered that many other diseases should be studied at the national and sub-national levels.

• Journal of Animal Science and Technology
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• 제50권1호
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• pp.27-32
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• 2008

본 연구의 목적은 1990년 1월부터 2006년 12월사이에 경주한 9,934두의 주파기록, 총 209,725개를 이용하여 국내 더러브렛 경주마의 유전적 개량량을 추정하는데 있다. 주파기록에 대한 연간 표현형 개량량은 1,000m, 1,400m 이하, 1,700m 이상의 경주거리와 전체 자료에서 각각 －0.148초, －0.137초, －0.137초와 －0.139초였으며, 모든 경주거리에서 감소 추세를 나타내었다. 경주년도별 환경효과의 추세는 모든 경주거리에서 표현형 추세와 거의 일치하였으며, 영구환경효과와 기수효과의 추세는 거의 나타나지 않았다. 연간 유전적 개량량은 1,000 m와 전체 자료에서 각각 －0.037과 －0.030초로 다소 낮은 수치였으나 일괄적인 감소 추세를 나타내었다. 따라서 경주마의 질적 향상을 위한 개량계획을 설정하는 것이 시급한 과제라 생각된다.

• Asian Pacific Journal of Cancer Prevention
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• 제13권12호
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• pp.6245-6250
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• 2012

Background: With increase in life expectancy, adoption of newer lifestyles and screening using prostate specific antigen (PSA), the incidence of prostate cancer is on rise. Globally prostate cancer is the second most frequently diagnosed cancer and sixth leading cause of cancer death in men. The present communication makes an attempt to analyze the time trends in incidence for different age groups of the Indian population reported in different Indian registries using relative difference and regression approaches. Materials and Methods: The data published in Cancer Incidence in Five Continents for various Indian registries for different periods and/or publications by the individual registries served as the source materials. Trends were estimated by computing the mean annual percentage change (MAPC) in the incidence rates using the relative difference between two time periods (latest and oldest) and also by estimation of annual percentage change (EAPC) by the Poisson regression model. Results: Age adjusted incidence rates (AAR) of prostate cancer for the period 2005-2008 ranged from 0.8 (Manipur state excluding Imphal west) to 10.9 (Delhi) per $10^5$ person-years. Age specific incidence rates (ASIR) increased in all PBCRs especially after 55 years showing a peak incidence at +65 years clearly indicating that prostate cancer is a cancer of the elderly. MAPC in crude incidence rate(CR) ranged from 0.14 (Ahmedabad) to 8.6 (Chennai). Chennai also recorded the highest MAPC of 5.66 in ASIR in the age group of 65+. Estimated annual percentage change (EAPC) in the AAR ranged from 0.8 to 5.8 among the three registries. Increase in trend was seen in the 55-64 year age group cohort in many registries and in the 35-44 age group in Metropolitan cities such as Delhi and Mumbai. Conclusions: Several Indian registries have revealed an increasing trend in the incidence of prostate cancer and the mean annual percentage change has ranged from 0.14-8.6.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2007년도 특별 심포지엄 논문집
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• pp.63-72
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• 2007

Current estimates of the ice-mass balance over the Greenland and the Antarctica using retrievals of time-varying gravity from GRACE are presented. Two different GRACE gravity data, UTCSR RL01 and UTCSR RL04, are used for the estimates to examine the impact of the relative accuracy of background models in the GRACE data processing for inter-annual variations of GRACE gravity data. In addition, the ice-mass balance is appraised from the conventional GRACE data, which represents global gravity, and the filtered GRACE data, which isolates the terrestrial gravity effect from GRACE gravity data. The former estimate shows that there exists similar negative trends of ice-mass balance over the Greenland from UTCSR RL01 and UTCSR RL04 while the time series from the both GRACE data over the Antarctica differ significantly from each other, and no apparent trends are observed. The result for the Greenland from the latter calculation is similar to the former estimate. However, the latter calculation presents positive trends of ice-mass balance for the Antarctica from both GRACE data. These results imply that residual oceanic geophysical signals, particularly for ocean tides, significantly corrupt the ice-mass estimate over the Antarctica as leakage error. In addition, the spatial alias of GRACE is likely to affect the ice-mass balance because the spatial spectrum of ocean tides is not conserved via GRACE sampling, and thus ocean tides contaminate terrestrial gravity signal. To minimize the alias effect, I suggest to use the combined gravity models from GRACE, SLR and polar motion.

• 디지털산업정보학회논문지
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• 제14권2호
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• pp.19-25
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• 2018

With the development of IT technology, various services such as artificial intelligence and autonomous vehicles are being introduced, and many changes are taking place in our lives. However, if secure security is not provided, it will cause many risks, so the information security becomes more important. In this paper, we analyzed the research trends of main themes of information security over time. In order to conduct the research, 'Information Security' was searched in the Web of Science database. Using the abstracts of theses published from 1991 to 2016, we derived main research topics through topic modeling and time series regression analysis. The topic modeling results showed that the research topics were Information technology, system access, attack, threat, risk management, network type, security management, security awareness, certification level, information protection organization, security policy, access control, personal information, security investment, computing environment, investment cost, system structure, authentication method, user behavior, encryption. The time series regression results indicated that all the topics were hot topics.