• Title/Summary/Keyword: match prediction

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Quantitative Analysis for Win/Loss Prediction of 'League of Legends' Utilizing the Deep Neural Network System through Big Data

  • No, Si-Jae;Moon, Yoo-Jin;Hwang, Young-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.213-221
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    • 2021
  • In this paper, we suggest the Deep Neural Network Model System for predicting results of the match of 'League of Legends (LOL).' The model utilized approximately 26,000 matches of the LOL game and Keras of Tensorflow. It performed an accuracy of 93.75% without overfitting disadvantage in predicting the '2020 League of Legends Worlds Championship' utilizing the real data in the middle of the game. It employed functions of Sigmoid, Relu and Logcosh, for better performance. The experiments found that the four variables largely affected the accuracy of predicting the match --- 'Dragon Gap', 'Level Gap', 'Blue Rift Heralds', and 'Tower Kills Gap,' and ordinary users can also use the model to help develop game strategies by focusing on four elements. Furthermore, the model can be applied to predicting the match of E-sports professional leagues around the world and to the useful training indicators for professional teams, contributing to vitalization of E-sports.

Sensitivity Analysis of Numerical Weather Prediction Model with Topographic Effect in the Radiative Transfer Process (복사전달과정에서 지형효과에 따른 기상수치모델의 민감도 분석)

  • Jee, Joon-Bum;Min, Jae-Sik;Jang, Min;Kim, Bu-Yo;Zo, Il-Sung;Lee, Kyu-Tae
    • Atmosphere
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    • v.27 no.4
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    • pp.385-398
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    • 2017
  • Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

Empirical Study on the Value Comparison Between Cosmic Radiation Measuring Instruments and Prediction Programs (항공기 탑재 우주방사선 측정장비와 예측프로그램의 비교값 실증연구)

  • Kyu-Wang Kim;Youn-Chul Choi
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.755-762
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    • 2023
  • The reliability of measuring instruments is essential in measuring cosmic radiation. To demonstrate this importance, this study measured and compared the amount of cosmic radiation using Liulin and TEPC, operated in South Korea, on a flight between Incheon, South Korea and LA, the US. In addition, since prior analysis based on a prediction program is necessary in advance to check the dose of cosmic radiation, this study utilized KREAM developed in Korea and the CARI-6M developed by the FAA to acquire the predicted value. As a result of the verification, the reliability of the two devices falls within the acceptable level of 20%, proving the reliability. Moreover, the differences between the values acquired by each prediction program were only subtle. Nevertheless, the analysis demonstrated that the prediction value obtained by the programs and the measured value had significant differences. Therefore, additional correction of the discrepancies or continuous research for such is required to match the predicted values are similar to the actual measured values.

Calibrating Thresholds to Improve the Detection Accuracy of Putative Transcription Factor Binding Sites

  • Kim, Young-Jin;Ryu, Gil-Mi;Park, Chan;Kim, Kyu-Won;Oh, Berm-Seok;Kim, Young-Youl;Gu, Man-Bok
    • Genomics & Informatics
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    • v.5 no.4
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    • pp.143-151
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    • 2007
  • To understand the mechanism of transcriptional regulation, it is essential to detect promoters and regulatory elements. Various kinds of methods have been introduced to improve the prediction accuracy of regulatory elements. Since there are few experimentally validated regulatory elements, previous studies have used criteria based solely on the level of scores over background sequences. However, selecting the detection criteria for different prediction methods is not feasible. Here, we studied the calibration of thresholds to improve regulatory element prediction. We predicted a regulatory element using MATCH, which is a powerful tool for transcription factor binding site (TFBS) detection. To increase the prediction accuracy, we used a regulatory potential (RP) score measuring the similarity of patterns in alignments to those in known regulatory regions. Next, we calibrated the thresholds to find relevant scores, increasing the true positives while decreasing possible false positives. By applying various thresholds, we compared predicted regulatory elements with validated regulatory elements from the Open Regulatory Annotation (ORegAnno) database. The predicted regulators by the selected threshold were validated through enrichment analysis of muscle-specific gene sets from the Tissue-Specific Transcripts and Genes (T-STAG) database. We found 14 known muscle-specific regulators with a less than a 5% false discovery rate (FDR) in a single TFBS analysis, as well as known transcription factor combinations in our combinatorial TFBS analysis.

Equivalent Dynamic Modeling of Coil Bundle for Prediction of Dynamic Properties of Stator in Small Motors (소형 전동기의 고정자 동특성 예측을 위한 코일 다발의 등가 동적 모형화)

  • 은희광;고홍석;김광준
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.540-545
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    • 2001
  • In case of small motors, coil bundle occupies a large portion of stator in view of mass and volume as well as dynamics. It is observed through modal test on the stator of an IPM BLDC (interior permanent magnet brushless direct current) motor that coil bundle wound on the stator core causes the first and second natural frequencies to decrease by about 20-30% compared with those of bare stator. Especially the third natural frequency is newly observed below 3 KHz, which is not observed on the bare stator. It is found that at the third mode the end-coil and the core vibrate out of phase in radial direction. In this paper, the stator is dynamically modeled in terms of the core and the coil bundle consisting of the end-coil and the slot coil based on the above observations for the prediction of dynamic properties. The core can easily be modeled using finite element method with its actual material properties and geometric shape. The concept of equivalent bending stiffness is used for modeling of the end-coil so that predictions may match with the measured natural frequencies for the end-coil cut out of the stator. Although the same concept can be applied to the slot coil, separation of the slot coil from the stator is impractical. Therefore, equivalent bending stiffness of the slot coil is determined through iterative comparisons with the measurements of natural frequencies of the stator with the slot coil in it.

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Predictive Study of Rubber Friction Considering Large Deformation Contact (대변형 접촉을 고려한 고무 마찰 예측 연구)

  • Nam, Seungkuk
    • Tribology and Lubricants
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    • v.34 no.1
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    • pp.1-8
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    • 2018
  • This paper presents the analysis of friction master curves for a sliding elastomer on rough granite. The hysteresis friction is calculated using an analytical model that considers the energy spent during the local deformation of the rubber due to surface asperities. The adhesion friction is also considered for dry friction prediction. The viscoelastic modulus of the rubber compound and the large-strain effective modulus are obtained from dynamic mechanical analysis (DMA). We accurately demonstrate the large strain of rubber that contacts with road substrate using the GW theory. We found that the rubber block deforms approximately to 40% strain. In addition, the viscoelastic master curve considering nonlinearity (at 40% strain) is derived based on the above finding. As viscoelasticity strongly depends on temperature, it can be assumed that the influence of velocity on friction is connected to the viscoelastic shift factors gained from DMA using the time-temperature superposition. In this study, we apply these shift factors to measure friction on dry granite over a velocity range for various temperatures. The measurements are compared to simulated hysteresis and adhesion friction using the Kluppel friction theory. Although friction results in the low-speed band match well with the simulation results, there are differences in the predicted and experimental results as the velocity increases. Thus, additional research is required for a more precise explanation of the viscoelastic material properties for better prediction of rubber friction characteristics.

User-to-User Matching Services through Prediction of Mutual Satisfaction Based on Deep Neural Network

  • Kim, Jinah;Moon, Nammee
    • Journal of Information Processing Systems
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    • v.18 no.1
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    • pp.75-88
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    • 2022
  • With the development of the sharing economy, existing recommender services are changing from user-item recommendations to user-user recommendations. The most important consideration is that all users should have the best possible satisfaction. To achieve this outcome, the matching service adds information between users and items necessary for the existing recommender service and information between users, so higher-level data mining is required. To this end, this paper proposes a user-to-user matching service (UTU-MS) employing the prediction of mutual satisfaction based on learning. Users were divided into consumers and suppliers, and the properties considered for recommendations were set by filtering and weighting. Based on this process, we implemented a convolutional neural network (CNN)-deep neural network (DNN)-based model that can predict each supplier's satisfaction from the consumer perspective and each consumer's satisfaction from the supplier perspective. After deriving the final mutual satisfaction using the predicted satisfaction, a top recommendation list is recommended to all users. The proposed model was applied to match guests with hosts using Airbnb data, which is a representative sharing economy platform. The proposed model is meaningful in that it has been optimized for the sharing economy and recommendations that reflect user-specific priorities.

Image Mixing in Multiview 3 Dimensional Imaging Systems (다시점 3차원 영상 시스템에서 영상혼합)

  • Kim, Shin-Hwan;Son, Jung-Young
    • Journal of Korea Multimedia Society
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    • v.11 no.2
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    • pp.175-181
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    • 2008
  • A 2 dimensional quality function for quantifying the quality of images observed at viewing regions in contact-type multiview 3 dimensional imaging systems is devised and its effectiveness is verified experimentally. The function allows calculating the locations of viewing regions for patched images of any number of different view images. The images observed at the calculated regions reveal that different parts of the display panel of the system project different view images and match with the function's prediction.

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COMPARISON OF CANDU DUPIC PHYSICS CODES WITH MCNP

  • Gyuhong Roh;Park, Hangbok
    • Proceedings of the Korean Nuclear Society Conference
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    • 1997.05a
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    • pp.65-70
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    • 1997
  • Computational benchmark calculations have been performed for CANDU DUPIC fuel lattice and core using a Monte Carlo code MCNP-4B with ENDF/B-V library. The eigenvalues of the DUPIC fuel lattice have been predicted by an integral transport code WIMS-AECL using ENDF/B-V library for different burnup steps and lattice conditions. The comparison has shown that the eigenvalues match those of MCNP-4B within 0.20% $\Delta$k difference between WIMS-AECL and MCNP-4B results. The calculation of a 2-dimensional CANDU core loaded with DUPIC fuel has shown that the eigenvalue predicted by a diffusion code RFSP using lattice parameters generated by WIMS-AECL matches that of MCNP-4B within 0.12%Δk and the largest bundle power prediction error is around 7.2%.

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Shape Prediction in Eulerian Analysis of Steady State Shape Rolling (정상상태 형상압연의 오일러리안 해석에서 형상 예측)

  • 이용신
    • Transactions of Materials Processing
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    • v.10 no.7
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    • pp.579-583
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    • 2001
  • Shape changes of a workpiece in an Eulerian Finite Element analysis for the steady state, three-roll-stand shape rolling are modelled. Although an Eulerian analysis has many advantages for the steady state rolling problems, it necessitates an assumption about the unknown shape of the control volume. In almost all cases, the assumed control volume does not match the final shape and the control volume should be updated. This update can be accomplished by performing a free surface correction. The final shape of a material point, which has a spherical shape at the inlet, can be also predicted by integrating a deformation gradient along a stream line. Analyses of three-roll-stand shape rolling are performed and the results are discussed in detail.

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