• 제목/요약/키워드: 컴퓨터 시스템

검색결과 15,119건 처리시간 0.04초

Parameter Sensitivity Analysis of VfloTM Model In Jungnang basin (중랑천 유역에서의 VfloTM 모형의 매개변수 민감도 분석)

  • Kim, Byung Sik;Kim, Bo Kyung;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • 제29권6B호
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    • pp.503-512
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    • 2009
  • Watershed models, which are a tool for water cycle mechanism, are classified as the distributed model and the lumped model. Currently, the distributed models have been more widely used than lumped model for many researches and applications. The lumped model estimates the parameters in the conceptual and empirical sense, on the other hand, in the case of distributed model the first-guess value is estimated from the grid-based watershed characteristics and rainfall data. Therefore, the distributed model needs more detailed parameter adjustment in its calibration and also one should precisely understand the model parameters' characteristics and sensitivity. This study uses Jungnang basin as a study area and VfloTM model, which is a physics-based distributed hydrologic model, is used to analyze its parameters' sensitivity. To begin with, 100 years frequency-design rainfall is derived from Huff's method for rainfall duration of 6 hours, then the discharge is simulated using the calibrated parameters of VfloTM model. As a result, hydraulic conductivity and overland's roughness have an effect on runoff depth and peak discharge, respectively, while channel's roughness have influence on travel time and peak discharge.

Trends in the use of big data and artificial intelligence in the sports field (스포츠 현장에서의 빅데이터와 인공지능 활용 동향)

  • Seungae Kang
    • Convergence Security Journal
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    • 제22권2호
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    • pp.115-120
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    • 2022
  • This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

Exploring the Job Competencies of Data Scientists Using Online Job Posting (온라인 채용정보를 이용한 데이터 과학자 요구 역량 탐색)

  • Jin, Xiangdan;Baek, Seung Ik
    • The Journal of Society for e-Business Studies
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    • 제27권2호
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    • pp.1-20
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    • 2022
  • As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

A Study on DID-based Vehicle Component Data Collection Model for EV Life Cycle Assessment (전기차 전과정평가를 위한 DID 기반 차량부품 데이터수집 모델 연구)

  • Jun-Woo Kwon;Soojin Lee;Jane Kim;Seung-Hyun Seo
    • KIPS Transactions on Computer and Communication Systems
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    • 제12권10호
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    • pp.309-318
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    • 2023
  • Recently, each country has been moving to introduce an LCA (Life Cycle Assessment) to regulate greenhouse gas emissions. The LCA is a mean of measuring and evaluating greenhouse gas emissions generated over the entire life cycle of a vehicle. Reliable data for each electric vehicle component is needed to increase the reliability of the LCA results. To this end, studies on life cycle evaluation models using blockchain technology have been conducted. However, in the existing model, key product information is exposed to other participants. And each time parts data information is updated, it must be recorded in the blockchain ledger in the form of a transaction, which is inefficient. In this paper, we proposed a DID(Decentralized Identity)-based data collection model for LCA to collect vehicle component data and verify its validity effectively. The proposed model increases the reliability of the LCA by ensuring the validity and integrity of the collected data and verifying the source of the data. The proposed model guarantees the validity and integrity of collected data. As only user authentication information is shared on the blockchain ledger, the model prevents indiscriminate exposure of data and efficiently verifies and updates the source of data.

An Experiment for Surface Soil Moisture Mapping Using Sentinel-1 and Sentinel-2 Image on Google Earth Engine (Google Earth Engine 제공 Sentinel-1과 Sentinel-2 영상을 이용한 지표 토양수분도 제작 실험)

  • Jihyun Lee ;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • 제39권5_1호
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    • pp.599-608
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    • 2023
  • The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

LAN Based MFD Interface for Integrated Operation of Radio Facilities using Fishery Vessel (어선용 무선설비의 통합운용을 위한 LAN 기반 MFD 인터페이스)

  • In-ung Ju;In-suk Kang;Jeong-yeon Kim;Seong-Real Lee;Jo-cheon Choi
    • Journal of Advanced Navigation Technology
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    • 제26권6호
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    • pp.496-503
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    • 2022
  • In the reality that the fishing population is decreasing and the single-man fishing vessels is increasing, mandatory equipment for navigation and radio equipments for the safety of fishing boats has continued to be added. Therefore, many equipment such as navigation, communication and fishing are installed in the narrow steering room, so it is very confusing and a number of monitors are placed in the front, which is a factor that degrades the function of maritime observation. To solve this problem, we studied an interface that integrates and operates to major radio facilities such as very high frequency-digital selective calling equipment (VHF-DSC), automatic identification system (AIS) and fishing boat location transmission device (V-pass) into one multi function display (MFD) based on LAN. In addition, IEC61162-450 UDP packets and IEC61162 sentence were applied to exchange data through link between MFD and radio equipments, and additional messages needed for each equipment and function were defined. The integrated MFD monitor is easily operated by the menu method, and the performance of the interface was evaluated by checking the distress and emergency communication functions related to maritime safety and the message transmission status by equipment.

Soil Moisture Estimation Using KOMPSAT-3 and KOMPSAT-5 SAR Images and Its Validation: A Case Study of Western Area in Jeju Island (KOMPSAT-3와 KOMPSAT-5 SAR 영상을 이용한 토양수분 산정과 결과 검증: 제주 서부지역 사례 연구)

  • Jihyun Lee;Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • 제39권6_1호
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    • pp.1185-1193
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    • 2023
  • The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

A Design of Timestamp Manipulation Detection Method using Storage Performance in NTFS (NTFS에서 저장장치 성능을 활용한 타임스탬프 변조 탐지 기법 설계)

  • Jong-Hwa Song;Hyun-Seob Lee
    • Journal of Internet of Things and Convergence
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    • 제9권6호
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    • pp.23-28
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    • 2023
  • Windows operating system generates various logs with timestamps. Timestamp tampering is an act of anti-forensics in which a suspect manipulates the timestamps of data related to a crime to conceal traces, making it difficult for analysts to reconstruct the situation of the incident. This can delay investigations or lead to the failure of obtaining crucial digital evidence. Therefore, various techniques have been developed to detect timestamp tampering. However, there is a limitation in detection if a suspect is aware of timestamp patterns and manipulates timestamps skillfully or alters system artifacts used in timestamp tampering detection. In this paper, a method is designed to detect changes in timestamps, even if a suspect alters the timestamp of a file on a storage device, it is challenging to do so with precision beyond millisecond order. In the proposed detection method, the first step involves verifying the timestamp of a file suspected of tampering to determine its write time. Subsequently, the confirmed time is compared with the file size recorded within that time, taking into consideration the performance of the storage device. Finally, the total capacity of files written at a specific time is calculated, and this is compared with the maximum input and output performance of the storage device to detect any potential file tampering.

A Study on the Artificial Intelligence-Based Soybean Growth Analysis Method (인공지능 기반 콩 생장분석 방법 연구)

  • Moon-Seok Jeon;Yeongtae Kim;Yuseok Jeong;Hyojun Bae;Chaewon Lee;Song Lim Kim;Inchan Choi
    • Journal of Korea Society of Industrial Information Systems
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    • 제28권5호
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    • pp.1-14
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    • 2023
  • Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.

A Study on the Application of Task Offloading for Real-Time Object Detection in Resource-Constrained Devices (자원 제약적 기기에서 자율주행의 실시간 객체탐지를 위한 태스크 오프로딩 적용에 관한 연구)

  • Jang Shin Won;Yong-Geun Hong
    • KIPS Transactions on Computer and Communication Systems
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    • 제12권12호
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    • pp.363-370
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    • 2023
  • Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.