• Title/Summary/Keyword: Cloud platform

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A study about a convergence development plan of MOOCs based e-learning in university (MOOCs에 기반한 대학이러닝의 융복합적 발전방안에 관한 연구)

  • Choi, Mi-Na;Roh, Hye-Lan
    • Journal of Digital Convergence
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    • v.13 no.7
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    • pp.9-21
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    • 2015
  • Nowadays, within the paradigm shift of e-learning, MOOCs service has been expanded among a number of global leading universities and this has affected our domestic universities' e-learning to look for different possibilities and new challenges. In consideration of our domestic educational condition, it is required to contemplate how university e-learning can be changed and developed with focus on MOOCs from the perspective of convergence development. This study suggests plans for convergence development in university e-learning based on MOOCs with conceptual model. We conducted the studies on relevant literature of university e-learning and MOOCs, expert consultation, SWOT analysis, survey for those involved of e-learning centers, etc. Through this process, we developed a final plan which integrates 'open advanced education course service', 'teaching and learning curation service', 'teaching and learning practice service', 'creative teaching and instruction method development and sharing service', and 'cloud based educational platform support service', etc with the perspective of convergence development. Also we designed convergence development plan based on MOOCs. It is assumed that the result of this research provides advanced plans for development of university e-learning and the base for further discussion of introduction and application of MOOCs service in domestic university.

Analysis and Forecasting for ICT Convergence Industries (ICT 융합 산업의 현황 및 전망)

  • Jang, Hee S.;Park, Jong T.
    • Journal of Service Research and Studies
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    • v.5 no.2
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    • pp.15-24
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    • 2015
  • The trade balance for the information and communications technology (ICT) industries in 2014 have reached 863 hundred million dollars as the main export products such as smart phone and semi-conductor increase, since the ICT industries have played an important role in economic growth in Korea. Until now, the consistent supporting of government and investment of company have been doing with the growth of ICT industries, as a result, Korea marked as the first in the UN electronic government preparing index, and rank 12 in the network preparing index through the policy of national information and basic plan of inter-industry convergence. However, as the unstable international economic circumstances, ICT industries is faced with the stagnation, and then preemptive development of products and services for ICT convergence industries is needed to continually get definite ICT Korea image. In this paper, the ICT convergence industry is analyzed and forecasted. In specific, the international and domestic market for cloud, 3D convergence, and internet of things is diagnosed. The market for ICT convergence industries is predicted to be 3.6 trillion dollar in the world, and 110 trillion won in domestic. From the analytical results for technology and services development, the preemptive supporting of the technology development and policy for the internet of things and 3D convergence industries is required. In addition to, through the future forecasting by socio-tech matrix method, the policy supporting for the ICT convergence area of healthcare, fintech, artificial intelligence, body platform, and human security is needed.

Development of Web Service for Liver Cirrhosis Diagnosis Based on Machine Learning (머신러닝기반 간 경화증 진단을 위한 웹 서비스 개발)

  • Noh, Si-Hyeong;Kim, Ji-Eon;Lee, Chungsub;Kim, Tae-Hoon;Kim, KyungWon;Yoon, Kwon-Ha;Jeong, Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.10
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    • pp.285-290
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    • 2021
  • In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

Method of ChatBot Implementation Using Bot Framework (봇 프레임워크를 활용한 챗봇 구현 방안)

  • Kim, Ki-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.1
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    • pp.56-61
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    • 2022
  • In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

A Hybrid Blockchain-Based E-Voting System with BaaS (BaaS를 이용한 하이브리드 블록체인 기반 전자투표 시스템)

  • Kang Myung Joe;Kim Mi Hui
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.8
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    • pp.253-262
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    • 2023
  • E-voting is a concept that includes actions such as kiosk voting at a designated place and internet voting at an unspecified place, and has emerged to alleviate the problem of consuming a lot of resources and costs when conducting offline voting. Using E-voting has many advantages over existing voting systems, such as increased efficiency in voting and ballot counting, reduced costs, increased voting rate, and reduced errors. However, centralized E-voting has not received attention in public elections and voting on corporate agendas because the results of voting cannot be trusted due to concerns about data forgery and modulation and hacking by others. In order to solve this problem, recently, by designing an E-voting system using blockchain, research has been actively conducted to supplement concepts lacking in existing E-voting, such as increasing the reliability of voting information and securing transparency. In this paper, we proposed an electronic voting system that introduced hybrid blockchain that uses public and private blockchains in convergence. A hybrid blockchain can solve the problem of slow transaction processing speed, expensive fee by using a private blockchain, and can supplement for the lack of transparency and data integrity of transactions through a public blockchain. In addition, the proposed system is implemented as BaaS to ensure the ease of type conversion and scalability of blockchain and to provide powerful computing power. BaaS is an abbreviation of Blockchain as a Service, which is one of the cloud computing technologies and means a service that provides a blockchain platform ans software through the internet. In this paper, in order to evaluate the feasibility, the proposed system and domestic and foreign electronic voting-related studies are compared and analyzed in terms of blockchain type, anonymity, verification process, smart contract, performance, and scalability.

Threat Situation Determination System Through AWS-Based Behavior and Object Recognition (AWS 기반 행위와 객체 인식을 통한 위협 상황 판단 시스템)

  • Ye-Young Kim;Su-Hyun Jeong;So-Hyun Park;Young-Ho Park
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.4
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    • pp.189-198
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    • 2023
  • As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

Oil Spill Monitoring in Norilsk, Russia Using Google Earth Engine and Sentinel-2 Data (Google Earth Engine과 Sentinel-2 위성자료를 이용한 러시아 노릴스크 지역의 기름 유출 모니터링)

  • Minju Kim;Chang-Uk Hyun
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.311-323
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    • 2023
  • Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.

Implementation of IoT-Based Irrigation Valve for Rice Cultivation (벼 재배용 사물인터넷 기반 물꼬 구현)

  • Byeonghan Lee;Deok-Gyeong Seong;Young Min Jin;Yeon-Hyeon Hwang;Young-Gwang Kim
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.93-98
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    • 2023
  • In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.

Telemedicine Protocols for the Management of Patients with Acute Spontaneous Intracerebral Hemorrhage in Rural and Medically Underserved Areas in Gangwon State : Recommendations for Doctors with Less Expertise at Local Emergency Rooms

  • Hyo Sub Jun;Kuhyun Yang;Jongyeon Kim;Jin Pyeong Jeon;Sun Jeong Kim;Jun Hyong Ahn;Seung Jin Lee;Hyuk Jai Choi;In Bok Chang;Jeong Jin Park;Jong-Kook Rhim;Sung-Chul Jin;Sung Min Cho;Sung-Pil Joo;Seung Hun Sheen;Sang Hyung Lee
    • Journal of Korean Neurosurgical Society
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    • v.67 no.4
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    • pp.385-396
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    • 2024
  • Previously, we reported the concept of a cloud-based telemedicine platform for patients with intracerebral hemorrhage (ICH) at local emergency rooms in rural and medically underserved areas in Gangwon state by combining artificial intelligence and remote consultation with a neurosurgeon. Developing a telemedicine ICH treatment protocol exclusively for doctors with less ICH expertise working in emergency rooms should be part of establishing this system. Difficulties arise in providing appropriate early treatment for ICH in rural and underserved areas before the patient is transferred to a nearby hub hospital with stroke specialists. This has been an unmet medical need for decades. The available reporting ICH guidelines are realistically applicable in university hospitals with a well-equipped infrastructure. However, it is very difficult for doctors inexperienced with ICH treatment to appropriately select and deliver ICH treatment based on the guidelines. To address these issues, we developed an ICH telemedicine protocol. Neurosurgeons from four university hospitals in Gangwon state first wrote the guidelines, and professors with extensive ICH expertise across the country revised them. Guidelines and recommendations for ICH management were described as simply as possible to allow more doctors to use them easily. We hope that our effort in developing the telemedicine protocols will ultimately improve the quality of ICH treatment in local emergency rooms in rural and underserved areas in Gangwon state.

Creation of Actual CCTV Surveillance Map Using Point Cloud Acquired by Mobile Mapping System (MMS 점군 데이터를 이용한 CCTV의 실질적 감시영역 추출)

  • Choi, Wonjun;Park, Soyeon;Choi, Yoonjo;Hong, Seunghwan;Kim, Namhoon;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1361-1371
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    • 2021
  • Among smart city services, the crime and disaster prevention sector accounted for the highest 24% in 2018. The most important platform for providing real-time situation information is CCTV (Closed-Circuit Television). Therefore, it is essential to create the actual CCTV surveillance coverage to maximize the usability of CCTV. However, the amount of CCTV installed in Korea exceeds one million units, including those operated by the local government, and manual identification of CCTV coverage is a time-consuming and inefficient process. This study proposed a method to efficiently construct CCTV's actual surveillance coverage and reduce the time required for the decision-maker to manage the situation. For this purpose, first, the exterior orientation parameters and focal lengths of the pre-installed CCTV cameras, which are difficult to access, were calculated using the point cloud data of the MMS (Mobile Mapping System), and the FOV (Field of View) was calculated accordingly. Second, using the FOV result calculated in the first step, CCTV's actual surveillance coverage area was constructed with 1 m, 2 m, 3 m, 5 m, and 10 m grid interval considering the occluded regions caused by the buildings. As a result of applying our approach to 5 CCTV images located in Uljin-gun, Gyeongsnagbuk-do the average re-projection error was about 9.31 pixels. The coordinate difference between calculated CCTV and location obtained from MMS was about 1.688 m on average. When the grid length was 3 m, the surveillance coverage calculated through our research matched the actual surveillance obtained from visual inspection with a minimum of 70.21% to a maximum of 93.82%.