• Title/Summary/Keyword: Measuring Space

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Evaluation of Concentration and Reaction Kinetics through Color Analyses (색상 분석법을 이용한 농도 및 촉매반응속도 측정)

  • Lee, Euna;Chang, Ji Woong
    • Applied Chemistry for Engineering
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    • v.33 no.3
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    • pp.279-283
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    • 2022
  • UV-vis spectroscopy is one of the powerful tools for measuring the concentrations of reactant and products during a chemical reaction. However, there is an limitation of using the technique when the reaction undergoes in high concentration and high temperature. Color analysis using camera images can provide the identical results with UV-vis analysis with regardless of the sample concentration and temperature. The catalytic reduction reaction of resazurin to resorufin was investigated using the color analysis with the color spaces such as CIE L*a*b*. Moreover, the color analysis enabled the independent analysis of two different material's concentrations without the deconvolution of overlapped wavelengths unlike the case of using UV-vis spectroscopy.

Large Storage Performance and Optimization Study using blockwrite (blockwrite를 이용한 대형 스토리지 성능 측정 및 최적화 연구)

  • Kim, Hyo-Ryoung;Song, Min-Gyu;Kang, Yong-Woo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1145-1152
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    • 2021
  • In order to optimize the performance of 1.4P large storage, the characteristics of each chunk mode were investigated, and the chunk 512K mode was selected in terms of I/O speed. NVME storage system was configured and used to measure data server performance of large storage. By measuring the change in throughput according to the number of threads of the 1.4P large storage, the characteristics of the large storage system were identified, and it was confirmed that the performance was up to 133Gbps with a block size of 32KB. As a result of data transmission/reception experiment using globus-url-copy of GridFTP, it was found that this large storage has a throughput of 33Gbps.

A Study on Fire Dynamics Simulation on the Arrangement of Aero System in the Residential (주거공간 에어로 시스템 배치에 관한 화재시뮬레이션 연구)

  • Choi, Doo Chan;Ko, Min Hyeok;Lee, Doo Hee;Park, Kye Won;Choi, Jeong Min;Lee, Yong Kwon;Kim, Gil Nam;Sun, Kyoung Soo
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.890-896
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    • 2021
  • Purpose: The called Aero System is important to find the well detected place in the livingroom or bedroom so, it needs to the confirmation through the Fire Dynamics Simulation Method: A fire simulation of a residential space of 59 m2 was performed, and in order to find the point where the fire environment was exposed quickly, measuring points were installed at 0.6 m and 1.5 m in height for each bedroom and living room, and the point where the fire was quickly detected was confirmed. Result: It was confirmed that the temperature and carbon monoxide sensor set at a point of 1.5 m was quickly detected at the reference value. Conclusion: The Fire detection would be relatively quick if the product in which the fire extinguishing module and the AQI module were separated was installed on the wall.

Proposal of Optimized Neural Network-Based Wireless Sensor Node Location Algorithm (최적화된 신경망 기반 무선 센서 노드위치 알고리즘 제안)

  • Guan, Bo;Qu, Hongxiang;Yang, Fengjian;Li, Hongliang;Yang-Kwon, Jeong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1129-1136
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    • 2022
  • This study leads to the shortcoming that the RSSI distance measurement method is easily affected by the external environment and the position error is large, leading to the problem of optimizing the distance values measured by the RSSI distance measurement nodes in this three-dimensional configuration environment. We proposed the CA-PSO-BP algorithm, which is an improved version of the CA-PSO algorithm. The proposed algorithm allows setting unknown nodes in WSN 3D space. In addition, since CA-PSO was applied to the BP neural network, it was possible to shorten the learning time of the BP network and improve the convergence speed of the algorithm through learning. Through the algorithm proposed in this study, it was proved that the precision of the network location can be increased significantly (15%), and significant results were obtained.

A Study on the Classification of Fault Motors using Sound Data (소리 데이터를 이용한 불량 모터 분류에 관한 연구)

  • Il-Sik, Chang;Gooman, Park
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.885-896
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    • 2022
  • Motor failure in manufacturing plays an important role in future A/S and reliability. Motor failure is detected by measuring sound, current, and vibration. For the data used in this paper, the sound of the car's side mirror motor gear box was used. Motor sound consists of three classes. Sound data is input to the network model through a conversion process through MelSpectrogram. In this paper, various methods were applied, such as data augmentation to improve the performance of classifying fault motors and various methods according to class imbalance were applied resampling, reweighting adjustment, change of loss function and representation learning and classification into two stages. In addition, the curriculum learning method and self-space learning method were compared through a total of five network models such as Bidirectional LSTM Attention, Convolutional Recurrent Neural Network, Multi-Head Attention, Bidirectional Temporal Convolution Network, and Convolution Neural Network, and the optimal configuration was found for motor sound classification.

Impact Sensitivity and Friction Sensitivity of HTPB Based Propellant According to the Aluminum Content (HTPB 계열 추진제의 알루미늄 함량에 따른 충격감도 및 마찰감도 연구)

  • Kim, Kahee;Park, Jung-Ho
    • Journal of the Korean Society of Propulsion Engineers
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    • v.25 no.6
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    • pp.60-65
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    • 2021
  • In this paper, we examined the ignition possibility of the propellant depending on its non-uniform composition of aluminum. Impact and friction sensitivity was investigated by arbitrarily changing the aluminum content in the range of 14~20% to simulate the non-uniform distribution of aluminum in the propellant. As a result of measuring the impact sensitivity, the 50% ignition energy and minimum ignition energy have values around 50 J regardless of the aluminum content. This means that the propellant does not become sensitive to impact even if the aluminum content is increased. On the other hand, the friction sensitivity result shows that as the aluminum content increases, the 50% ignition force and minimum ignition forces were decreased, and thus the propellant becomes sensitive. "Hot Spot" model of propellant ignition is applied, the space inside the propellant is momentarily compressed and ignited by friction stimuli rather than by impact stimuli.

Proposal for a Sensory Integration Self-system based on an Artificial Intelligence Speaker for Children with Developmental Disabilities: Pilot Study

  • YeJin Wee;OnSeok Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1216-1233
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    • 2023
  • Conventional occupational therapy (OT) is conducted under the observation of an occupational therapist, and there are limitations in measuring and analyzing details such as degree of hand tremor and movement tendency, so this important information may be lost. It is therefore difficult to identify quantitative performance indicators, and the presence of observers during performance sometimes makes the subjects feel that they have to achieve good results. In this study, by using the Unity3D and artificial intelligence (AI) speaker, we propose a system that allows the subjects to steadily use it by themselves and helps the occupational therapist objectively evaluate through quantitative data. This system is based on the OT of the sensory integration approach. And the purpose of this system is to improve children's activities of daily living by providing various feedback to induce sensory integration, which allows them to develop the ability to effectively use their bodies. A dynamic OT cognitive assessment tool for children used in clinical practice was implemented in Unity3D to create an OT environment of virtual space. The Leap Motion Controller allows users to track and record hand motion data in real time. Occupational therapists can control the user's performance environment remotely by connecting Unity3D and AI speaker. The experiment with the conventional OT tool and the system we proposed was conducted. As a result, it was found that when the system was performed without an observer, users can perform spontaneously and several times feeling ease and active mind.

Artificial neural network model for predicting sex using dental and orthodontic measurements

  • Sandra Anic-Milosevic;Natasa Medancic;Martina Calusic-Sarac;Jelena Dumancic;Hrvoje Brkic
    • The korean journal of orthodontics
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    • v.53 no.3
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    • pp.194-204
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    • 2023
  • Objective: To investigate sex-specific correlations between the dimensions of permanent canines and the anterior Bolton ratio and to construct a statistical model capable of identifying the sex of an unknown subject. Methods: Odontometric data were collected from 121 plaster study models derived from Caucasian orthodontic patients aged 12-17 years at the pretreatment stage by measuring the dimensions of the permanent canines and Bolton's anterior ratio. Sixteen variables were collected for each subject: 12 dimensions of the permanent canines, sex, age, anterior Bolton ratio, and Angle's classification. Data were analyzed using inferential statistics, principal component analysis, and artificial neural network modeling. Results: Sex-specific differences were identified in all odontometric variables, and an artificial neural network model was prepared that used odontometric variables for predicting the sex of the participants with an accuracy of > 80%. This model can be applied for forensic purposes, and its accuracy can be further improved by adding data collected from new subjects or adding new variables for existing subjects. The improvement in the accuracy of the model was demonstrated by an increase in the percentage of accurate predictions from 72.0-78.1% to 77.8-85.7% after the anterior Bolton ratio and age were added. Conclusions: The described artificial neural network model combines forensic dentistry and orthodontics to improve subject recognition by expanding the initial space of odontometric variables and adding orthodontic parameters.

Evaluation of multiple-satellite precipitation data by rainfall intensity (다중 위성 강수자료의 강우강도별 특성 평가)

  • Kim, Kiyoung;Lee, Seulchan;Choi, Minha;Jung, Sungho;Yeon, Minho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.383-383
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    • 2021
  • 강수는 수자원 분석 및 지리학적 연구에 가장 핵심적으로 쓰이는 수문인자이며, 최근 기후변화와 방재 관련한 다양한 연구에서 정확한 강수자료의 중요성이 부각되고 있다. 특히, 강수는 지표에서의 유출, 침투, 증발 등 다양한 수문현상으로 이어지므로, 수문순환, 물수지 분석에 있어 강우강도 등 강수 발생 양상과 유형에 대한 정확한 자료는 필수불가결하다. 강수량은 Automatic Weather Station (AWS)을 통해 비교적 정확하게 측정되고 있으나, 이러한 계측자료는 기상학적, 지형적 영향을 크게 받으며 대표성이 좁다는 단점을 가지고 있어 유출 및 기후 등 공간적 범위를 대상으로 한 연구에 활용하기에 한계점을 가지고 있다. 이러한 한계점을 극복하기 위해 지상강우레이더를 통한 국지적 강수자료 및 인공위성 기반 전 지구적 강수 관측 자료가 활용되고 있다. 특히 인공위성을 활용한 강우 측정방법은 미계측 유역에서 수자원 측정 및 관리 계획을 세우거나 전 지구적으로 장기적 변화를 분석하는데 있어 가장 활용도가 높다. National Aeronautics and Space Administration (NASA)의 Tropical Rainfall Measuring Mission (TRMM)을 포함한 기존 강수측정 보조 위성에 더하여 2014년 Global Precipitation Measurement (GPM) 핵심 위성이 발사된 이후 다양한 기관에서 여러 인공위성을 결합한 강수 산출물들을 제공하고 있다(NASA-IMERG, JAXA-GSMAP, NOAA-CMORPH). 본 연구에서는 세 가지 위성 기반 강수 자료의 산출 알고리즘을 비교□분석하고, 강우강도에 따른 산출물들의 정확도를 평가하였다. 본 연구결과는 높은 강우강도 발생 시 나타나는 위성 강수자료의 불확실성을 개선하는 데 기여할 수 있을 것으로 판단되며, 이후 신뢰도 높은 다중 위성 융합 강수 산출물을 구현하기 위한 바탕이 될 것으로 기대된다.

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A novel method for testing accuracy of bite registration using intraoral scanners

  • Lydia Kakali;Demetrios J. Halazonetis
    • The korean journal of orthodontics
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    • v.53 no.4
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    • pp.254-263
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    • 2023
  • Objective: The evidence on the accuracy of bite registration using intraoral scanners is sparse. This study aimed to develop a new method for evaluating bite registration accuracy using intraoral scanners. Methods: Two different types of models were used; 10 stone models and 10 with acrylic resin teeth. A triangular frame with cylindrical posts at each apex (one anterior and two posteriors) was digitally designed and manufactured using three-dimensional (3D) printing. Such a structure was fitted in the lingual space of each maxillary and mandibular model so that, in occlusion, the posts would contact their opposing counterparts, enforcing a small interocclusal gap between the two arches. This ensured no tooth interference and full contact between opposing posts. Bite registration accuracy was evaluated by measuring the distance between opposing posts, with small values indicating high-accuracy. Three intraoral scanners were used: Medit i500, Primescan, and Trios 4. Viewbox software was used to measure the distance between opposing posts and compute roll and pitch. Results: The average maximum error in interocclusal registration exceeded 50 ㎛. Roll and pitch orientation errors ranged above 0.1 degrees, implying an additional interocclusal error of around 40 ㎛ or more. The models with acrylic teeth exhibited higher errors. Conclusions: A method that avoids the need for reference hardware and the imprecision of locating reference points on tooth surfaces, and offers simplicity in the assessment of bite registration with an intraoral scanner, was developed. These results suggest that intraoral scanners may exhibit clinically significant errors in reproducing the interocclusal relationships.