• Title/Summary/Keyword: Machine-to-machine (M2M)

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Fracture strength of tie wings in a newly-developed polycarbonate bracket (국산 폴리카보네이트 브라켓 윙의 파절 강도에 관한 연구)

  • Sun, Min-Kyu;Lee, Ki-Heon;Hwang, Hyeon-Shik
    • The korean journal of orthodontics
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    • v.37 no.3 s.122
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    • pp.204-211
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    • 2007
  • Objective: With an increasing demand for esthetic orthodontic appliances, the interest in polycarbonate brackets has also increased. However, polycarbonate bracket wings are prone to fracture. The purpose of this study was to evaluate the clinical usefulness of a newly-developed polycarbonate bracket by measuring the fracture strength of bracket tie wings. Methods: Alice (K.M. Daicom, Seoul, Korea) and Spirit MB (Ormco, Glendora, CA, USA) brackets were used as an experimental and control bracket respectively. Each bracket group was divided into halves. One half was untreated and the other half was treated with 2,000 times of thermocycling between $5^{\circ}C\;and\;55^{\circ}C$. The fracture strength of the wing was measured by a universal testing machine. Results: Alice bracket wings showed significantly higher strength than Spirit MB bracket wings in both untreated and thermocycled bracket cases. Conclusion: Alice brackets may be used clinically in terms of the strength of bracket wings.

Rotor Failures Diagnosis of Squirrel Cage Induction Motors with Different Supplying Sources

  • Menacer, Arezki;Champenois, Gerard;Nait Said, Mohamed Said;Benakcha, Abdelhamid;Moreau, Sandrine;Hassaine, Said
    • Journal of Electrical Engineering and Technology
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    • v.4 no.2
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    • pp.219-228
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    • 2009
  • The growing application and the numerous qualities of induction motors (1M) in industrial processes that require high security and reliability levels has led to the development of multiple methods for early fault detection. However, various faults can occur, such as stator short-circuits and rotor failures. Traditionally the diagnosis machine is done through a sinusoidal power supply, in the present paper we study experimentally the effects of the rotor failures, such as broken rotor bars in function of the ac supplying, the load and show the impact of the converter from diagnosis of the machine. The technique diagnosis used is based on the spectral analysis of stator currents or stator voltages respectively according to the types of induction motor ac supplying. So, four different ac supplying are considered: ${\odot}$ the IM is directly by the balanced three-phase network voltage source, ${\odot}$ the IM is fed by a sinusoidal current source given the controlled by hysteresis, ${\odot}$ the IM is fed (in open loop) by a scalar control imposing through ratio V/f=constant, ${\odot}$ the IM is controlled through a vector control using space vector pulse width modulation (SVPWM) technique inverter with an outer speed loop.

Thermal Characteristics of Daegu using Land Cover Data and Satellite-derived Surface Temperature Downscaled Based on Machine Learning (기계학습 기반 상세화를 통한 위성 지표면온도와 환경부 토지피복도를 이용한 열환경 분석: 대구광역시를 중심으로)

  • Yoo, Cheolhee;Im, Jungho;Park, Seonyoung;Cho, Dongjin
    • Korean Journal of Remote Sensing
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    • v.33 no.6_2
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    • pp.1101-1118
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    • 2017
  • Temperatures in urban areas are steadily rising due to rapid urbanization and on-going climate change. Since the spatial distribution of heat in a city varies by region, it is crucial to investigate detailed thermal characteristics of urban areas. Recently, many studies have been conducted to identify thermal characteristics of urban areas using satellite data. However,satellite data are not sufficient for precise analysis due to the trade-off of temporal and spatial resolutions.In this study, in order to examine the thermal characteristics of Daegu Metropolitan City during the summers between 2012 and 2016, Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data at 1 km spatial resolution were downscaled to a spatial resolution of 250 m using a machine learning method called random forest. Compared to the original 1 km LST, the downscaled 250 m LST showed a higher correlation between the proportion of impervious areas and mean land surface temperatures in Daegu by the administrative neighborhood unit. Hot spot analysis was then conducted using downscaled daytime and nighttime 250 m LST. The clustered hot spot areas for daytime and nighttime were compared and examined based on the land cover data provided by the Ministry of Environment. The high-value hot spots were relatively more clustered in industrial and commercial areas during the daytime and in residential areas at night. The thermal characterization of urban areas using the method proposed in this study is expected to contribute to the establishment of city and national security policies.

Development of Line Standards Measurement System Using an Optical Microscope (광학 현미경을 이용한 선표준물 측정 시스템 개발)

  • Kim, Jong-Ahn;Kim, Jae-Wan;Kang, Chu-Shik;Eom, Tae-Bong
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.8
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    • pp.72-78
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    • 2009
  • We developed a line standards measurement system using an optical microscope and measured two kinds of line standards. It consists of three main parts: an optical microscope module including a CCD camera, a stage system with a linear encoder, and a measurement program for a microscopic image processing. The magnification of microscope part was calibrated using one-dimensional gratings and the angular motion of stage was measured to estimate the Abbe error. The threshold level in line width measurement was determined by comparing with certified values of a line width reference specimen, and its validity was proved through the measurement of another line width specimen. The expanded uncertainty (k=2) was about 100 nm in the measurements of $1{\mu}m{\sim}10{\mu}m$ line width. In the comparison results of line spacing measurement, two kinds of values were coincide within the expanded uncertainty, which were obtained by the one-dimensional measuring machine in KRISS and the line standards measurement system. The expanded uncertainty (k=2) in the line spacing measurement was estimated as $\sqrt{(0.098{\mu}m)^2+(1.8{\times}10^{-4}{\times}L)^2}$. Therefore, it will be applied effectively to the calibration of line standards, such as line width and line spacing, with the expanded uncertainty of several hundreds nanometer.

A Quantitative Approach to Minimize Energy Consumption in Cloud Data Centres using VM Consolidation Algorithm

  • M. Hema;S. KanagaSubaRaja
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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    • pp.312-334
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    • 2023
  • In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

Data-driven Model Prediction of Harmful Cyanobacterial Blooms in the Nakdong River in Response to Increased Temperatures Under Climate Change Scenarios (기후변화 시나리오의 기온상승에 따른 낙동강 남세균 발생 예측을 위한 데이터 기반 모델 시뮬레이션)

  • Gayeon Jang;Minkyoung Jo;Jayun Kim;Sangjun Kim;Himchan Park;Joonhong Park
    • Journal of Korean Society on Water Environment
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    • v.40 no.3
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    • pp.121-129
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    • 2024
  • Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

A Study on the Application of Acoustic Emission Measurement for the In-process Detection of Milling Tools' Wear and Chipping (밀링 공구마멸과 치핑의 검출을 위한 음향방출 이용에 관한 연구)

  • Yoon, J.H.;Kang, M.S.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.11 no.1
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    • pp.31-37
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    • 1991
  • Acoustic emission(AE) signals detected during metal cutting were applied as the experimental test to sensing tool wear and chipping on the NC vertical milling machine. The in-process detection of cutting tool wear including chipping, cracking and fracture has been investigated by means of AE in spite of vibration or noise through intermittent metal cutting, then the following results were obtained 1) When the tool wear is increased suddenly, or the amplitude of AE signals changes largely, it indicates chipping or breaking of the insert tip. 2) It was confirmed that AE signal is highly sensitive to the cutting speed and tool wear. 3) At the early period of cutting, the wear were large and RMS value increased highly by the influence of minute chipping and cracking, etc. Therefore, the above situations should be considered for the time when the tool would be changed.

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PRODUCTION PLANNING IN FUZZY ENVIRONMENT

  • M, H-A
    • Journal of applied mathematics & informatics
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    • v.6 no.2
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    • pp.417-432
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    • 1999
  • This paper describes a fuzzy system designed to support production planning in an industrial unit producing cardboard boxes. In this industrial unit orders for n boxes of width w, length l, height h, made of q layers of type k paper for delivery in t units of time are produced. In the production of such orders apart from meeting the orders specifications it is usually tried to minimize the margin trim loss the number of machine setups and the holding cost of the finished orders. Considering the dynamism of production systems that are influenced by such factors as market demand fluctuations changes in commercial priorities raw material availability and pro-ducation capabilities we solve this multi-objective problem by fuzzy set theory.

Lot-Streaming Flow Shop Problem with Delivery Windows (딜리버리 윈도우 로트-스트리밍 흐름 공정 문제)

  • Yoon, Suk-Hun
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.2
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    • pp.159-164
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    • 2004
  • Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots and then scheduling these sublots in order to accelerate the completion of jobs in a multi-stage production system. Anew genetic algorithm (NGA) is proposed for an-job, m-machine, equal-size sublot lot-streaming flow shop scheduling problem with delivery windows in which the objective is to minimize the mean weighted absolute deviation of job completion times from due dates. The performance of NGA is compared with that of an adjacent pairwise interchange (API) method and the results of computational experiments show that NGA works well for this type of problem.

Effect of Die Casting Condition on the Mechanical Properties of AZ91HP Mg Alloy (AZ91HP 마그네슘합금의 기계적성질에 미치는 다이캐스팅 조건의 영향)

  • Ahn, Yong-Sik;Klein, F.
    • Journal of Korea Foundry Society
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    • v.22 no.4
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    • pp.155-159
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    • 2002
  • Magnesium alloys have high strength to weight ratio and are extremely attractive for applications in transport industry. Most of structural magnesium alloys are manufactured by die casting process. The tensile properties of AZ91HP magnesium alloy were investigated after die casting under various die casting conditions. After die casting by using cold chamber machine, the volume porosity of specimens was examined with density method. With the increase of the volume porosity of specimens, both the tensile strength and elongation were significantly decreased, however the 0.2% offset strength was almost independent of the amount of porosity. With the increase of crystal pressure from 500 to 900 bar during die casting, the volume porosity was decreased, which resulted in the increase of the tensile strength. The mould temperature within the range of $150{\sim}250^{\circ}C$ has not influenced the microstructure with the eutectic phase and tensile properties of specimens. The tensile strength was the highest at 90m/sec of gate speed.