• Title/Summary/Keyword: Internet resources

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Development of Software-Defined Perimeter-based Access Control System for Security of Cloud and IoT System (Cloud 및 IoT 시스템의 보안을 위한 소프트웨어 정의 경계기반의 접근제어시스템 개발)

  • Park, Seung-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.2
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    • pp.15-26
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    • 2021
  • Recently, as the introduction of cloud, mobile, and IoT has become active, there is a growing need for technology development that can supplement the limitations of traditional security solutions based on fixed perimeters such as firewalls and Network Access Control (NAC). In response to this, SDP (Software Defined Perimeter) has recently emerged as a new base technology. Unlike existing security technologies, SDP can sets security boundaries (install Gateway S/W) regardless of the location of the protected resources (servers, IoT gateways, etc.) and neutralize most of the network-based hacking attacks that are becoming increasingly sofiscated. In particular, SDP is regarded as a security technology suitable for the cloud and IoT fields. In this study, a new access control system was proposed by combining SDP and hash tree-based large-scale data high-speed signature technology. Through the process authentication function using large-scale data high-speed signature technology, it prevents the threat of unknown malware intruding into the endpoint in advance, and implements a kernel-level security technology that makes it impossible for user-level attacks during the backup and recovery of major data. As a result, endpoint security, which is a weak part of SDP, has been strengthened. The proposed system was developed as a prototype, and the performance test was completed through a test of an authorized testing agency (TTA V&V Test). The SDP-based access control solution is a technology with high potential that can be used in smart car security.

ECG Compression and Transmission based on Template Matching (템플릿 매칭 기반의 심전도 압축 전송)

  • Lee, Sang-jin;Kim, Sang-kon;Kim, Tae-kon
    • Journal of Internet Computing and Services
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    • v.23 no.1
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    • pp.31-38
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    • 2022
  • An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling (텍스트 마이닝과 토픽모델링 활용한 사회서비스 품질의 학술연구 동향 분석)

  • Lee, Hae-Jung;Youn, Ki-Hyok
    • Journal of Internet of Things and Convergence
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    • v.8 no.3
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    • pp.29-40
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    • 2022
  • The aim of this study was to analyze research trends of social service quality from 2007 to 2020 based on text mining and topic modeling. Our focus was to provide foundational materials for social service improvement by discovering the latent meaning of relevant research papers. We collected 97 scholarly articles on social service, social welfare service, and quality from RISS, and implemented two segments of text mining analysis. Our results showed that the first section included 38 papers and the second 59, indicating 6.9 articles annually. Word frequency results demonstrated that the common keywords of both sections were 'service', 'quality', 'social service', 'satisfaction', 'users', 'quality control', 'reuse', 'policy', 'voucher', etc. TF-IDF suggested that 'social service', 'satisfaction', 'users', 'customer satisfaction', 'revisiting', 'voucher', 'quality', 'assisted living facility', 'quality control', 'community service investment business', etc., were represented in both categories. Lastly, topic modeling analysis revealed that the first segment displayed 'types of care services', 'service costs', 'reuse', 'users based', and 'job creation', whereas the second presented 'service quality', 'public value', 'management system of human resources', 'service provision system', and 'service satisfaction'. Future directions of social service quality were discussed based on the results.

A Study on Creation of Fair Transaction Environment between Platform Operator and Contents Provider in Broadcasting Industry (방송 산업 내 플랫폼사업자와 콘텐츠사업자 간 공정거래환경 조성 연구)

  • Yonghee Kim;Joonho Do
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.2
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    • pp.175-183
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    • 2023
  • In a broadcasting market environment that has a close interdependence between platform operators and content operators, problems such as conflicts over program usage fees, and home shopping transmission fees are intensifying. This study attempted to analyze the environment of the domestic broadcasting market and present implications, analyze the cause of user fee conflict between the platform and PP, and propose detailed alternatives to resolve user fee conflict disputes. The results of environmental analysis on the domestic broadcasting market are as follows. First, the growth engine of the broadcasting industry has changed to direct resources such as service usage fees and content fees, and commerce is increasing. Second, as hegemony in the domestic broadcasting market changes from terrestrial to paid broadcasting and OTT, monopolies in the entire broadcasting area are being dismantled by voluntary entry. Third, the need to overhaul the existing regulatory system is increasing due to the dismantling and reorganization of the existing broadcasting market. On the other hand, this study proposed a strategy to diversify the profit structure of PP, supply program after pre-contracting, and strengthen CPS bargaining power in order to resolve disputes between paid broadcasting platforms and PP sharply. In particular, as strategies to strengthen CPS bargaining power of small and medium-sized SOs, it proposed to jointly improve CPS-related systems through IPTV and individual SOs, to redefine fees for programs and to voluntarily use programs.

TGC-based Fish Growth Estimation Model using Gaussian Process Regression Approach (가우시안 프로세스 회귀를 통한 열 성장 계수 기반의 어류 성장 예측 모델)

  • Juhyoung Sung;Sungyoon Cho;Da-Eun Jung;Jongwon Kim;Jeonghwan Park;Kiwon Kwon;Young Myoung Ko
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.61-69
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    • 2023
  • Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

A Study on the Performance Measurement and Analysis on the Virtual Memory based FTL Policy through the Changing Map Data Resource (멥 데이터 자원 변화를 통한 가상 메모리 기반 FTL 정책의 성능 측정 및 분석 연구)

  • Hyun-Seob Lee
    • Journal of Internet of Things and Convergence
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    • v.9 no.1
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    • pp.71-76
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    • 2023
  • Recently, in order to store and manage big data, research and development of a high-performance storage system capable of stably accessing large data have been actively conducted. In particular, storage systems in data centers and enterprise environments use large amounts of SSD (solid state disk) to manage large amounts of data. In general, SSD uses FTL(flash transfer layer) to hide the characteristics of NAND flash memory, which is a medium, and to efficiently manage data. However, FTL's algorithm has a limitation in using DRAM more to manage the location information of NAND where data is stored as the capacity of SSD increases. Therefore, this paper introduces FTL policies that apply virtual memory to reduce DRAM resources used in FTL. The virtual memory-based FTL policy proposed in this paper manages the map data by using LRU (least recently used) policy to load the mapping information of the recently used data into the DRAM space and store the previously used information in NAND. Finally, through experiments, performance and resource usage consumed during data write processing of virtual memory-based FTL and general FTL are measured and analyzed.

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.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
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    • v.14 no.2
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    • pp.125-135
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    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

Development of Prediction Model for Yard Tractor Working Time in Container Terminal (컨테이너 터미널 야드 트랙터 작업시간 예측 모형 개발)

  • Jae-Young Shin;Do-Eun Lee;Yeong-Il Kim
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2023.05a
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    • pp.57-58
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    • 2023
  • The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.

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An Empirical Study on the Adoption of Online Direct Marketing in Agricultural Firms (농업경영체의 온라인 직거래 마케팅 수용에 관한 실증적 연구)

  • Cheolho Yoon;Changhee Park
    • Information Systems Review
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    • v.20 no.1
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    • pp.41-59
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    • 2018
  • This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.