• Title/Summary/Keyword: Improving Efficiency

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A Comparison Analysis of Life Cycle Cost (LCC) of Pumps - In the Focus on Comparison of Excellent and General Products in Water Industry - (Pump의 생애주기 비용(LCC) 비교 분석 - 물산업 우수제품과 일반제품의 비교를 중심으로 -)

  • Park, Woopyung;Choi, Yong;Jeon, Si Young;Kim, Jinho;Kang, Seongmi
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.3
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    • pp.66-73
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    • 2022
  • In order to induce users to purchase excellent products in the water industry that satisfy the technical standards of excellent products, in this study, it is to present the advantages of the cost aspect of the pumps as the objective basis. It will be to promote technology development of domestic water companies and to create a virtuous cycle structure in the water industry. In order to present an objective basis for the merits in terms of cost, an economic evaluation was conducted through life cycle cost analysis. For the LCC analysis, initial cost (pump cost and installation cost), operation cost (energy cost and maintenance cost) and demolition cost (disposal cost and residual value) are searched and calculated. As the results of comparison on two capacity of pumps, the energy cost of the excellent pump is 212 million KRW lower than the that of general pump in the large pump. The cost of excellent pump was 17 million KRW lower than that of general pump in small capacity pump. As the results of sensibility test, if the product is developed in the direction of improving pump efficiency and increasing the replacement cycle of consumables, it is predicted that the effect on LCC will be large.

A Evaluation of Fire Behavior According to Member Thickness of Precast Prestressed Hollow Core Slab of Fire Resistance Section (프리캐스트 프리스트레스트 내화단면 중공슬래브의 부재두께에 따른 화재거동평가 )

  • Yoon-Seob Boo;Kyu-Woong Bae;Sang-Min Shin
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.1
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    • pp.1-8
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    • 2023
  • At construction sites, interest in the production of precast materials is increasing due to off-site conditions due to changes in construction site conditions due to increased labor costs and the Act on the Punishment of Serious Accidents. In particular, the precast prestressed hollow slab has a hollow shape in the cross section, so structural performance is secured by reducing weight and controlling deflection through stranded wires. With the application of structural standards, the urgency of securing fire resistance performance is emerging. In this study, a fire-resistance cross section was developed by reducing the concrete filling rate in the cross section and improving the upper and lower flange shapes by optimizing the hollow shape in the cross section of the slab to have the same or better structural performance and economic efficiency compared to the existing hollow slab. The PC hollow slab to which this was applied was subjected to a two-hour fire resistance test using the cross-sectional thickness as a variable, and as a result of the test, fire resistance performance (load bearing capacity, heat shielding property, flame retardance property) was secured. Based on the experimental results, it is determined that fire resistance modeling can be established through numerical analysis simulation, and prediction of fire resistance analysis is possible according to the change of the cross-sectional shape in the future.

Degradation of Antibiotics Using Silver Decorated Heterojunction Carbon Nitride under Visible Light (은 장식 이종접합 질화탄소를 이용한 가시광선 조건에서의 항생제 분해 연구)

  • Taeyoon, Lee
    • Journal of the Korean GEO-environmental Society
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    • v.24 no.3
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    • pp.23-27
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    • 2023
  • Graphitic carbon nitride (g-C3N4) has been used as effective photocatalyst for degradation of antibiotics under visible light irradiation. However, the fast recombination of hole-electron pair may limit their photocatalytic efficiency. In our study, Ag was grafted on g-C3N4/g-C3N4 isotype heterojunction by a microwave-assisted decomposition method. The structure and physical properties of heterojunction photocatalyst were characterized through X-ray diffraction, UV-DRS, FT-IR, and Photoluminescence analyses. Ag decorated g-C3N4/g-C3N4 isotype heterojunction exhibited excellent photocatalytic activity for degradation of sulfamethoxazole under irradiation under visible light irradiation within 210 min, which is higher than g-C3N4/g-C3N4 isotype heterojunction and bulk g-C3N4. The addition of Ag may broaden the visible light absorption and restrict the recombination of hole-electron pair because of the surface plasmons resonance, resulting in the improving the photocatalytic activity.

Prediction of Music Generation on Time Series Using Bi-LSTM Model (Bi-LSTM 모델을 이용한 음악 생성 시계열 예측)

  • Kwangjin, Kim;Chilwoo, Lee
    • Smart Media Journal
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    • v.11 no.10
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    • pp.65-75
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    • 2022
  • Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

A Simulation Study for Improving Operations of an Emergency Medical Center (응급진료센터 운영 개선을 위한 시뮬레이션)

  • Mo, Chang-Woo;Choi, Seong-Hoon
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.35-45
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    • 2009
  • Emergency medical center(EMC) is the place for patients who need medical treatment immediately due to a disease, childbirth, or all sorts of accidents. Currently, most of EMCs use temporary beds because regular EMC beds cannot afford to serve all incoming patients. However, since it decreases the quality of service(QoS) of EMC patients and their guardians and efficiency of the EMC, some improvements are highly required to diminish the usage of temporary beds. The system duration time is one of the typical QoSs. This thesis proposes the information which is critical to make a better decision for cut down the number of temporary beds without sacrificing QoS of patients. The key point is to control the duration time of medical treatments for the consultation and hospitalization process, since it is the major reason of overcrowding in EMC and the usage of temporary beds. In this paper, we proposed an Arena simulation model reflecting real world substantially. Arena is one of the most widely accepted simulation softwares in the world. Using the developed model, we can obtain the optimal EMC operation parameters through simulation experiments. Optquest, included in the Arena, is used to make the developed simulation model collaborate with an optimization model. The results showed one can determine the set of optimal operation parameters decreasing the required number of temporary beds without deteriorating EMC patient's QoS.

Development of a low-power remote monitoring module for set-net fish school based on WCDMA (WCDMA 기반의 저전력 정치망 어군 정보전송 모듈 개발)

  • Donggil LEE;Myungsung KOO;Gyeom HEO;Jiwon CHEONG;Hyohyuc IM;Jaehyun BAE
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.59 no.3
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    • pp.206-214
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    • 2023
  • Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%

Digital Twin-based Cadastral Resurvey Performance Sharing Platform Design and Implementation (디지털트윈 기반의 지적재조사 성과공유 플랫폼 설계 및 구현)

  • Kim, IL
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.1
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    • pp.37-46
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    • 2023
  • As real estate values rise, interest in cadastral resurvey is increasing. Accordingly, a cadastral resurvey project is actively underway for drone operation through securing work efficiency and improving accuracy. The need for utilization and management of cadastral resurvey results (drone images) is being raised, and through this study, a 3D spatial information platform was developed to solve the existing drone image management and utilization limitations and to provide drone image-based 3D cadastral information. It is proposed to build and use. The study area was selected as a district that completed the latest cadastral resurvey project in which the study was organized in February 2023. Afterwards, a web-based 3D platform was applied to the study to solve the user's spatial limitations, and the platform was designed and implemented based on drone images, spatial information, and attribute information. Major functions such as visualization of cadastral resurvey results based on 3D information and comparison of performance between previous cadastral maps and final cadastral maps were implemented. Through the open platform established in this study, anyone can easily utilize the cadastral resurvey results, and it is expected to utilize and share systematic cadastral resurvey results based on 3-dimensional information that reflects the actual business district. In addition, a continuous management plan was proposed by integrating the distributed results into one platform. It is expected that the usability of the 3D platform will be further improved if a platform is established for the whole country in the future and a service linked to the cadastral resurvey administrative system is established.

Development of a Compound Classification Process for Improving the Correctness of Land Information Analysis in Satellite Imagery - Using Principal Component Analysis, Canonical Correlation Classification Algorithm and Multitemporal Imagery - (위성영상의 토지정보 분석정확도 향상을 위한 응용체계의 개발 - 다중시기 영상과 주성분분석 및 정준상관분류 알고리즘을 이용하여 -)

  • Park, Min-Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4D
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    • pp.569-577
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    • 2008
  • The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

Data-Driven Technology Portfolio Analysis for Commercialization of Public R&D Outcomes: Case Study of Big Data and Artificial Intelligence Fields (공공연구성과 실용화를 위한 데이터 기반의 기술 포트폴리오 분석: 빅데이터 및 인공지능 분야를 중심으로)

  • Eunji Jeon;Chae Won Lee;Jea-Tek Ryu
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.71-84
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    • 2021
  • Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

Outlier Detection and Labeling of Ship Main Engine using LSTM-AutoEncoder (LSTM-AutoEncoder를 활용한 선박 메인엔진의 이상 탐지 및 라벨링)

  • Dohee Kim;Yeongjae Han;Hyemee Kim;Seong-Phil Kang;Ki-Hun Kim;Hyerim Bae
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.125-137
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    • 2022
  • The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.