• Title/Summary/Keyword: Accuracy improvement

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Alcohol content analysis for Takju, a representative traditional liquor in Korea (대한민국 대표 전통주 탁주의 알코올 도수 분석)

  • Oh, Chang-Hwan
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.631-636
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    • 2022
  • Alcohol content, which is an important standard for Takju, a traditional multiple parallel fermentation liquor called makgeolli, is a factor that can affect the flavor. For alcohol content analysis, the distillation/hydrometry technique is mainly used. In this study, we analyzed the alcohol content of 14 commercially available Takju by the distillation/hydrometry technique and the improved GC method, respectively, after verifying the reliability of improved GC method. The precision and accuracy of the GC method were satisfactory, and LOQ and LOD were evaluated as 0.5% and 0.1% of ethanol contents, respectively. Among the three Takju exceeding the labelled alcohol content ±1, one Takju was quantitated as alcohol content 9.9% (by GC method) and 10.1% (distillation/hydrometry technique) exceeding labelled 6.0%. It was within the analytical error range of alcohol content for other two Takju, where the alcohol contents were exceeded -1.1%. The average precision (%RSD) of 14 Takju analyzed by the distillation/hydrometry technique (36.2%) and the GC method (12.8%), confirming that the GC method was better than the other. The improved GC method was evaluated to be effective in managing and improving the alcohol content standard of Takju with the wide range of alcohol content.

Personalized Speech Classification Scheme for the Smart Speaker Accessibility Improvement of the Speech-Impaired people (언어장애인의 스마트스피커 접근성 향상을 위한 개인화된 음성 분류 기법)

  • SeungKwon Lee;U-Jin Choe;Gwangil Jeon
    • Smart Media Journal
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    • v.11 no.11
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    • pp.17-24
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    • 2022
  • With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

Prediction of Chemical Acceleration Durability Time of Polymer Membrane in Polymer Electrolyte Membrane Fuel Cells (고분자 전해질 연료전지에서 고분자막의 화학적 가속 내구 시간 예측)

  • Sohyeong Oh;Donggeun Yoo;Sunggi Jung;Jihong Jeong;Kwonpil Park
    • Korean Chemical Engineering Research
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    • v.61 no.1
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    • pp.26-31
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    • 2023
  • For durability improvement of polymer electrolyte membrane fuel cell (PEMFC) polymer membrane, accelerated durability evaluation methods that can evaluate durability in a short time have been researched and developed. However, the lifespan of fuel cells for large commercial vehicles such as trucks and buses is more than three times that of passenger cars, and the chemical accelerated stress test (AST) time is also longer, reaching 1,500 hours or more. Therefore, in this study, as a method to evaluate the chemical durability of a membrane within a short time, it was examined whether the durability could be predicted by the pristine membrane characteristics. Hydrogen crossover current density (HCCD) and short resistance (SR) were estimated as initial characteristics, and AST time was predicted through the Fenton experiment, which was possible as an out-of-cell experiment for 3 hours. As the HCCD and fluoride ion emission concentration increased, the AST time tended to be linearly shortened, but there was a deviation (R2 ≒0.65). When the SR decreased, the AST time showed a linear increase, and the accuracy was high (R2 =0.93), so the AST time could be predicted with the initial SR of the membrane.

Attention based Feature-Fusion Network for 3D Object Detection (3차원 객체 탐지를 위한 어텐션 기반 특징 융합 네트워크)

  • Sang-Hyun Ryoo;Dae-Yeol Kang;Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.190-196
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    • 2023
  • Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

Prediction Method of Settlement Based on Field Monitoring Data for Soft Ground Under Preloading Improvement with Ramp Loading (점증 선행 하중으로 개량하는 연약지반의 계측기반 침하량 예측방법 개발)

  • Woo, Sang-Inn;Yune, Chan-Young;Baek, Seung-Kyung;Chung, Choong-Ki
    • Journal of the Korean Geotechnical Society
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    • v.24 no.10
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    • pp.83-91
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    • 2008
  • Previous settlement prediction methods based on settlement monitoring were developed under instantaneous loading condition and have restriction to be applied to soft ground under ramp loading condition. In this study, settlement prediction method under ramp loading was developed. New settlement prediction method under ramp loading considered influence factors of consolidation settlement such as thickness of clayed layer, quantity of surcharge load and preconsolidation pressure, etc. Geometrical correction method based on hyperbolic method (1991) and correction method based on probability theory were applied to increase accuracy of settlement prediction using field monitoring data after ramp loading. Large consolidation tests for ideally controlled one dimensional consolidation under ramp loading condition were performed and the settlement behavior was predicted based on the monitoring data. New prediction method yielded good result of entire settlement behavior by using data during an early stage of ramp load. Additionally, new prediction method offered better settlement prediction which had final settlement prediction in close proximity and low RMSE(Root Mean Square Error) than previous method such as hyperbolic method did.

Alternative Immunossays

  • Barnard, G.J.R.;Kim, J.B.;Collins, W.P.
    • Korean Journal of Animal Reproduction
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    • v.9 no.2
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    • pp.133-139
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    • 1985
  • An immunoassay may be defined as an analytical procedure involving the competitive reaction between a limiting concentration of specific antibody and two populations of antigen, one of which is labelled or immobillized. The advent of immunoassay has revolutionised our knowledge of reproductive physiology and the practice of veterinary and clinical medicine. Radioimmunoassay (RIA) was the first of these methods to be developed, which meausred the analyte with good sensitivity, accuracy and precision (1,2). The essential components of RIA are:-(i) a limited concentration of antibodies, (ii) a reference preparation, and (iii) an antigen labelled with a radioisotope (usually tritium or iodine-125). Most procedures invelove isolating the antibody-bound fraction and measuring the amount of labelled antigen. Good facilities are available for scintilltion counting, data reduction nd statistical analysis. RIA is undergoing refinement through:-(i) the introduction of new techniques to separate the antibody-bound and free fractions which minimize the misclassification of labelled antigen into these compartments, and the amount of non-specfic binding. (3), (ii) the development of non-extration for the measurement of haptens (4), (iii) the determination of a, pp.rent free (i.e. non-protein bound) analytes (5), and (iv) the use of monoclonal antibodies(6). In 1968, Miles and Hales introduced in important new type of immunoassay which they termed immunora-diometric assay (IRMA) based on t도 use of isotopically labelled specific antibodies(7) in a move from limited to excess reagent systems. The concept of two-site IRMAs (with a capture antibody on a solid-phase, and a second labelled antibody to a different antigenic determinant of the analyte) has enabled the development of more sensitive and less-time consuming methods for the measurement of protein hormones ovar wide concentration of analyte (8). The increasing use of isotopic methos for diverse a, pp.ications has exposed several problems. For example, the radioactive half-life and radiolysis of the labelled reagent limits assay sensitivity and imposes a time limit on the usefulness of a kit. In addition, the potential health hazards associated with the use and disposal of radioactive cmpounds and the solvents and photofluors necessary for liquid scientillation counting are incompatable with the development of extra-laboratory tests. To date, the most practical alternative labels to radioisotopes, for the measurement of analytes in a concentration > 1 ng/ml, are erythrocytes, polystyrene particiles, gold sols, dyes and enzymes or cofactors with a visual or colorimetric end-point(9). Increased sensitivity to<1 pg/ml may be obtained with fluorescent and chemiluminescent labels, or enzymes with a fluorometric, chemiluminometric or bioluminometric end-point. The sensitivity of any immunoassay or immunometric assay depends on the affinity of the antibody-antigen reaction, the specific activity of the label, the precision with which the reagents are manipulated and the nonspecific background signal (10). The sensitivity of a limited reagent system for the measurement of haptens or proteins is mainly dependent upon the affinity of the antibodies and the smalleest amount of reagent that may be manipulated. Consequently, it is difficult in practice to improve on the sensitivity obtained with iodine-125 as the label. Conversely, with excess reagent systems for the measurement of proteins it is theoretically possible to increase assay sensitivity at least 1000 fold with alternative luminescent labels. To date, a 10-fold improvement has been achieved, and attempts are being made to reduce the influence of other variables on the specific signal from the immunoreaction.

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Algorithm for Correcting Error in Smart Card Data Using Bus Information System Data (버스정보시스템 데이터를 활용한 교통카드 정류장 정보 오류 보정 알고리즘)

  • Hye Inn Song;Hwa Jeong Tak;Kang Won Shin;Sang Hoon Son
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.131-146
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    • 2023
  • Smart card data is widely used in the public transportation field. Despite the inevitability of various errors occur during the data collection and storage; however, smart card data errors have not been extensively studied. This paper investigates inherent errors in boarding and alighting station information in smart card data. A comparison smart card data and bus boarding and alighting survey data for the same time frame shows that boarding station names differ by 6.2% between the two data sets. This indicates that the error rate of smart card data is 6.2% in terms of boarding station information, given that bus boarding and alighting survey data can be considered as ground truth. This paper propose 6-step algorithm for correcting errors in smart card boarding station information, linking them to corresponding information in Bus Information System(BIS) Data. Comparing BIS data and bus boarding and alighting survey data for the same time frame reveals that boarding station names correspond by 98.3% between the two data sets, indicating that BIS data can be used as reliable reference for ground truth. To evaluate its performance, applying the 6-step algorithm proposed in this paper to smart card data set shows that the error rate of boarding station information is reduced from 6.2% to 1.0%, resulting in a 5.2%p improvement in the accuracy of smart card data. It is expected that the proposed algorithm will enhance the process of adjusting bus routes and making decisions related to public transportation infrastructure investments.

Structural Optimization and Improvement of Initial Weight Dependency of the Neural Network Model for Determination of Preconsolidation Pressure from Piezocone Test Result (피에조콘을 이용한 선행압밀하중 결정 신경망 모델의 구조 최적화 및 초기 연결강도 의존성 개선)

  • Kim, Young-Sang;Joo, No-Ah;Park, Hyun-Il;Park, Sol-Ji
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.3C
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    • pp.115-125
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    • 2009
  • The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

A Study on Evaluation and Improvement Plan for Applications for Smart-phone Overdependence Prevention (스마트폰 과의존 방지 애플리케이션 평가 및 서비스 주체별 개선방안 연구)

  • Gyoo Gun Lim;Hai Yan Jin;Hye min Hwang;Hye won Cho;Jae Ik Ahn
    • Journal of Service Research and Studies
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    • v.12 no.1
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    • pp.36-48
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    • 2022
  • As the use of smartphones has rapidly increased due to the development of digital technology, the expansion of smartphones, and the COVID-19 incident, dependence on smartphones and the Internet is emerging as a serious social problem. As one of the solutions to the smartphone overdependence problem, the government and companies are releasing smartphone overdependence prevention applications. However, research on the effectiveness of smartphone overdependence prevention applications is insufficient. Therefore, this study selects 25 applications serviced in Korea as analysis targets and evaluates smartphone overdependence prevention applications in terms of function and service using the FGI survey method to identify problems and propose improvements. In the function evaluation, the functions of blocking illegal/harmful apps/websites, limiting smartphone usage time, and monitoring smartphone usage status are provided in most applications, so satisfaction scores are also highly evaluated. However, functions such as location check, smombie prevention, and body camphishing prevention served by some applications are evaluated low due to poor performance and poor accuracy. Classified by service provider, government-providing applications need to accurately perform functions and improve convenience of use. Mobile-Carrier-providing applications need to improve connectivity with other carriers and compatibility with other smart devices like smartphone, tablet, etc. Other private enterprise-providing applications need to open AS channels such as customer service centre and chatbot to improve service.

Method and Reference Equipment for Evaluation of Travel Time Information (구간 통행시간정보 평가를 위한 기준장비 개발 및 평가 방법 연구)

  • Jeon, Hyeonmyeong;Cho, Yong-Sung;Ahn, Sun-Young;Lim, Sung Han
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.64-75
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    • 2022
  • The ITS performance evaluation has been performed in the evaluation of traffic data collection equipment. However, evaluation of the data collection equipment alone cannot guarantee the reliability of the traffic information. So, ITS service evaluation has to be implemented institutionally. In this study, an evaluation method has been prepared to evaluate the accuracy of travel time information in road sections. In addition, a piece of portable reference equipment was developed to collect travel time data on the road. Field tests were performed on two national road sections managed by the Seoul Construction and Management Administration (SCMA) to prepare an evaluation method considering field conditions and evaluate the reference equipment's performance. Based on the test results, the improvement of the reference equipment to collect more samples and the adjustment of collection points were discussed.