• Title/Summary/Keyword: Accuracy comparison

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A review and comparison of convolution neural network models under a unified framework

  • Park, Jimin;Jung, Yoonsuh
    • Communications for Statistical Applications and Methods
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    • v.29 no.2
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    • pp.161-176
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    • 2022
  • There has been active research in image classification using deep learning convolutional neural network (CNN) models. ImageNet large-scale visual recognition challenge (ILSVRC) (2010-2017) was one of the most important competitions that boosted the development of efficient deep learning algorithms. This paper introduces and compares six monumental models that achieved high prediction accuracy in ILSVRC. First, we provide a review of the models to illustrate their unique structure and characteristics of the models. We then compare those models under a unified framework. For this reason, additional devices that are not crucial to the structure are excluded. Four popular data sets with different characteristics are then considered to measure the prediction accuracy. By investigating the characteristics of the data sets and the models being compared, we provide some insight into the architectural features of the models.

Sustainability of pensions in Asian countries

  • Hyunoo, Shim;Siok, Kim;Yang Ho, Choi
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.679-694
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    • 2022
  • Mortality risk is a significant threat to individual life, and quantifying the risk is necessary for making a national population plan and is a traditionally fundamental task in the insurance and annuity businesses. Like other advanced countries, the sustainability of life pensions and the management of longevity risks are becoming important in Asian countries entering the era of aging society. In this study, mortality and pension value sustainability trends are compared and analyzed based on national population and mortality data, focusing on four Asian countries from 1990 to 2017. The result of analyzing the robustness and accuracy of generalized linear/nonlinear models reveals that the Cairns-Blake-Dowd model, the nonparametric Renshaw-Haberman model, and the Plat model show low stability. The Currie, CBD M5, M7, and M8 models have high stability against data periods. The M7 and M8 models demonstrate high accuracy. The longevity risk is found to be high in the order of Taiwan, Hong Kong, Korea, and Japan, which is in general inversely related to the population size.

Performance analysis and comparison of various machine learning algorithms for early stroke prediction

  • Vinay Padimi;Venkata Sravan Telu;Devarani Devi Ningombam
    • ETRI Journal
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    • v.45 no.6
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    • pp.1007-1021
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    • 2023
  • Stroke is the leading cause of permanent disability in adults, and it can cause permanent brain damage. According to the World Health Organization, 795 000 Americans experience a new or recurrent stroke each year. Early detection of medical disorders, for example, strokes, can minimize the disabling effects. Thus, in this paper, we consider various risk factors that contribute to the occurrence of stoke and machine learning algorithms, for example, the decision tree, random forest, and naive Bayes algorithms, on patient characteristics survey data to achieve high prediction accuracy. We also consider the semisupervised self-training technique to predict the risk of stroke. We then consider the near-miss undersampling technique, which can select only instances in larger classes with the smaller class instances. Experimental results demonstrate that the proposed method obtains an accuracy of approximately 98.83% at low cost, which is significantly higher and more reliable compared with the compared techniques.

A Comparison of Deep Learning Models for IQ Fingerprint Map Based Indoor Positioning in Ship Environments

  • Yootae Shin;Qianfeng Lin;Jooyoung Son
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.1122-1140
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    • 2024
  • The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

NUMERICAL STUDY OF THE SERIES SOLUTION METHOD TO ANALYSIS OF VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS

  • ASIYA ANSARI;NAJMUDDIN AHMAD;ALI HASAN ALI
    • Journal of applied mathematics & informatics
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    • v.42 no.4
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    • pp.899-913
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    • 2024
  • In this article, the Series Solution Method (SSM) is employed to solve the linear or non-linear Volterra integro-differential equations. Numerous examples have been presented to explain the numerical results, which is the comparison between the exact solution and the numerical solution, and it is found through the tables. The amount of error between the exact solution and the numerical solution is very small and almost nonexistent, and it is also illustrated through the graph how the exact solution completely applies to the numerical solution. This proves the accuracy of the method, which is the Series Solution Method (SSM) for solving the linear or non-linear Volterra integro-differential equations using Mathematica. Furthermore, this approach yields numerical results with remarkable accuracy, speed, and ease of use.

The Consolidation and Comparison Processes in Visual Working Memory Tested under Pattern-Backward Masking (역행 차폐를 통해 본 시각작업기억의 공고화 및 비교처리 과정)

  • Han, Ji-Eun;Hyun, Joo-Seok
    • Korean Journal of Cognitive Science
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    • v.22 no.4
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    • pp.365-384
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    • 2011
  • A recent study of visual working memory(VWM) under a change detection paradigm proposed an idea that the comparison process of VWM representations against incoming perceptual inputs can be performed more rapidly than the process of forming durable memory representations into VWM. To test this hypothesis, we compared the size of interference effect caused by pattern-backward masks following after either the sample(sample-mask condition) or test items (test-mask condition). In Experiment 1, subjects performed a color change detection task for four colored-boxes, and pattern masks with mask-onset asynchronies(MSOA) of either 64ms or 150ms followed each item location either after the sample or after the test items. The change detection accuracy was both comparable in the sample-mask condition regardless of the MSOAs, whereas the accuracy in the trials with a MSOA of 150ms was substantially higher than the MSOA of 65ms in the test-masking condition. In Experiment 2, we manipulated setsizes to 1, 2, 3, 4 items and also MSOAs to 117ms, 234ms, 350ms, 484ms and compared the pattern of interference across a variety of setsize and MSOA conditions. The sample-mask condition yielded a pattern of masking interference which became more evident as the setsize increases and as the MSOA was shorter. However, this pattern of interference was less apparent in the test-mask condition. These results indicate that the comparison process between remembered items in VWM and perceptual inputs is less vulnerable to interference from pattern-backward masking than VWM consolidation is, and thus support for the recent idea that the comparison process in VWM can be performed very fast and accurately.

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Comparison of Performance of Measuring Method of VIS/NIR Spectroscopic Spectrum to Predict Soluble Solids Content of 'Shingo' Pear (VIS/NIR 스펙트럼 측정모드에 따른 신고 배의 당도 예측성능 비교)

  • Suh, Sang-Ryong;Lee, Kyeong-Hwan;Yu, Seung-Hwa;Yoo, Soo-Nam;Choi, Yeong-Soo
    • Journal of Biosystems Engineering
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    • v.36 no.2
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    • pp.130-139
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    • 2011
  • Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.

Comparative study of prediction models for corporate bond rating (국내 회사채 신용 등급 예측 모형의 비교 연구)

  • Park, Hyeongkwon;Kang, Junyoung;Heo, Sungwook;Yu, Donghyeon
    • The Korean Journal of Applied Statistics
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    • v.31 no.3
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    • pp.367-382
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    • 2018
  • Prediction models for a corporate bond rating in existing studies have been developed using various models such as linear regression, ordered logit, and random forest. Financial characteristics help build prediction models that are expected to be contained in the assigning model of the bond rating agencies. However, the ranges of bond ratings in existing studies vary from 5 to 20 and the prediction models were developed with samples in which the target companies and the observation periods are different. Thus, a simple comparison of the prediction accuracies in each study cannot determine the best prediction model. In order to conduct a fair comparison, this study has collected corporate bond ratings and financial characteristics from 2013 to 2017 and applied prediction models to them. In addition, we applied the elastic-net penalty for the linear regression, the ordered logit, and the ordered probit. Our comparison shows that data-driven variable selection using the elastic-net improves prediction accuracy in each corresponding model, and that the random forest is the most appropriate model in terms of prediction accuracy, which obtains 69.6% accuracy of the exact rating prediction on average from the 5-fold cross validation.

A STUDY ON THE ACCURACY OF THE IMPRESSION BODY ACCORDING TO MATERIALS AND FORMS OF THE INDIVIDUAL TOOTH TRAY (개별 치아 트레이의 재료와 형태에 따른 인상체의 정밀성에 관한 연구)

  • Ryu, Duck-Woo;Lim, Ju-Hwan;Cho, In-Ho
    • The Journal of Korean Academy of Prosthodontics
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    • v.38 no.2
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    • pp.242-254
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    • 2000
  • Accurate impression is very important to achieve desirable prosthesis and there are many factors in taking a good impression. For example, types of impression material, types of impression tray, impression taking methods and so on. Recently individual tooth tray technique is accepted as obtaining good impression that can be applied to multiple abutment impression, heavy salivated patient, to minimize the effect of natural teeth s undercuts and to reduce pain during cord packing procedures. The purpose of this study was to compare the accuracy according to materials and forms of the individual tooth tray which is clinically applied nowadays. Used materials in experiment were divided into 3 types (acrylic resin. $Futar^{(R)}$ occlusion. $Blu-mousse^{(R)}$) and forms were divided into 2 types (forming occlusal vent hole or not and forming marginal vent space or not). Stone master model from impression body and metal master model were measured by $X-PLAN360d^{(R)}$ to compare occlusal surface discrepancy and marginal discrepancy. The results were as follows: 1. In comparison of occlusal surface discrepancy and marginal discrepancy according to materials, groups with three materials showed no statistical difference 2. In comparison of occlusal surface discrepancy and marginal discrepancy according to occlusal vent hole, groups with occlusal vent hole showed significantly less marginal discrepancy than groups with no occlusal vent hole(p<0.05). 3. In comparison of occlusal surface discrepancy and marginal discrepancy according to 0.5mm-marginal-vent-space, groups with no 0.5mm-marginal-vent-space showed significantly less marginal discrepancy than groups with 0.5mm-marginal-vent-space (p<0.05). In summary these results suggest that individual tooth tray made of 3 types of materials with occlusal vent hole and individual tooth tray made of acrylic resin with no marginal vent space showed good accuracy of impression. In addition, individual tooth tray which is made of bite registration materials may be more useful because of advantage in facility and timesaving aspect of fabrication.

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Research on Oriental Medicine Diagnosis and Classification System by Using Neck Pain Questionnaire (경항통 설문지를 이용한 한의학적 진단 및 분류체계에 관한 연구)

  • Song, In;Lee, Geon-Mok;Hong, Kwon-Eui
    • Journal of Acupuncture Research
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    • v.28 no.3
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    • pp.85-100
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    • 2011
  • Objectives : The purpose of this thesis is to help the preparation of oriental medicine clinical guidelines for drawing up the standards of oriental medicine demonstration and diagnosis classification about the neck pain. Methods : Statistical analysis about Gyeonghangtong(頸項痛), Nakchim(落枕), Sagyeong(斜頸), Hanggang (項强) classified experts' opinions about neck pain patients by Delphi method is conducted by using oriental medicine diagnosis questionnaire. The result was classified by using linear discriminant analysis (LDA), diagonal linear discriminant analysis (DLDA), diagonal quadratic discriminant analysis (DQDA), K-nearest neighbor classification (KNN), classification and regression trees (CART), support vector machines (SVM). Results : The results are summarized as follows. 1. The result analyzed by using LDA has a hit rate of 84.47% in comparison with the original diagnosis. 2. High hit rate was shown when the test for three categories such as Gyeonghangtong and Hanggang category, Sagyeong caterogy and Nakchim caterogy was conducted. 3. The result analyzed by using DLDA has a hit rate of 58.25% in comparison with the original diagnosis. The result analyzed by using DQDA has a accuracy of 57.28% in comparison with the original diagnosis. 4. The result analyzed by using KNN has a hit rate of 69.90% in comparison with the original diagnosis. 5. The result analyzed by using CART has a hit rate of 69.60% in comparison with the original diagnosis. There was a hit rate of 70.87% When the test of selected 8 significant questions based on analysis of variance was performed. 6. The result analyzed by using SVM has a hit rate of 80.58% in comparison with the original diagnosis. Conclusions : Statistical analysis using oriental medicine diagnosis questionnaire on neck pain generally turned out to have a significant result.