• Title/Summary/Keyword: Predicting Patterns

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Investigation of the Finite Planar Frequency Selective Surface with Defect Patterns

  • Hong, Ic-Pyo
    • Journal of Electrical Engineering and Technology
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    • v.9 no.4
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    • pp.1360-1364
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    • 2014
  • In this paper, RCS characteristics on defect pattern of crossed dipole slot FSS having a finite size have been analyzed. To analyze RCS, we applied the electric field integral equation analysis which applies BiCGSTab algorithm with iterative method and uses RWG basis function. To verify the validity of this paper, RCS of PEC sphere has been compared to the theoretical results and FSSs with defect patterns are fabricated and measured. As defect patterns in FSS, missing one column, missing some elements, and discontinuity in surfaces are simulated and compared with the measurement results. Resonant frequency shifts in pass band and changes in bandwidth are observed. From the results, precisely predicting and designing frequency characteristics over defect patterns are essential when applying FSS structures such as FSS radomes.

A Pattern-Based Prediction Model for Dynamic Resource Provisioning in Cloud Environment

  • Kim, Hyuk-Ho;Kim, Woong-Sup;Kim, Yang-Woo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.10
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    • pp.1712-1732
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    • 2011
  • Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

An Application of K-$\varepsilon$ Turbulence Model for Predicting Effect of a Rectanguler Obstacle with Heat Flux in a Solt-Ventilated Enclosure on Air Flow

  • 최홍림;김현태;김우중
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.34 no.E
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    • pp.30-44
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    • 1992
  • A modification of the TEACH-like computer program based on the k-$\varepsilon$ turbulence transport was applied for predicting air mixing patterns and temperature distributions in a rectangular, slot-ventilated enclosure having obstructions ; a rectangular obstacle with heat flux, solid walls separates the passage and the pig pens, and purlins beneath the ceiling. Air flow patterns were calculated for the cases with and without the purlin, extending 300mm beneath the ceiling. Comparisons of prediction data of Randall & Battams(1976) showed air flow pattern predicted well for the case without the purlin. Heat was accumulated at the corner of the left side of the solid wall and the right-upper region of the simulated pigs. However the air distribution pattern was completely different from data for the case with the purlin. The deviation from the observation may be attributed to the difference of the geometric configuation. Exploring the cause of the deviation should be conducted in a further study. Temperature stratification was also observed due to incomplete mixing. The obstruction in the route of the inlet air jet at inlet should be avoided since most of kinetic energy dissipates at the abstacle duet to impingement.

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Analysis of the urban flood pattern using rainfall data and measurement flood data (강우사상과 침수 실측자료를 이용한 도시침수 양상 관계분석)

  • Moon, Hye Jin;Cho, Jae Woong;Kang, Ho Seon;Lee, Han Seung;Hwang, Jeong Geun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.95-95
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    • 2020
  • Urban flooding occurs in the form of internal-water inundation on roads and lowlands due to heavy rainfall. Unlike in the case of rivers, inundation in urban areas there is lacking in research on predicting and warning through measurement data. In order to analyze urban flood patterns and prevent damage, it is necessary to analyze flooding measurement data for various rainfalls. In this study, the pattern of urban flooding caused by rainfall was analyzed by utilizing the urban flooding measuring sensor, which is being test-run in the flood prone zone for urban flooding management. For analysis, 2019 rainfall data, surface water depth data, and water level data of a street inlet (storm water pipeline) were used. The analysis showed that the amount of rainfall that causes flooding in the target area was identified, and the timing of inundation varies depending on the rainfall pattern. The results of the analysis can be used as verification data for the urban inundation limit rainfall under development. In addition, by using rainfall intensity and rainfall patterns that affect the flooding, it can be used as data for establishing rainfall criteria of urban flooding and predicting that may occur in the future.

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A Study on Predictors of Academic Achievement in College Students : Focused on J University (대학생의 학업성취도 예측요인 연구 : J 대학을 중심으로)

  • Son, Yo-Han;Kim, In-Gyu
    • The Journal of the Korea Contents Association
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    • v.20 no.1
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    • pp.519-529
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    • 2020
  • The purpose of this study is to establish a model for predicting academic achievement of college students and to reveal the interrelationship and relative influence of each factor. For this, we surveyed the personal factors and learning strategy factors of 1,310 learners at J University, and analyzed the discriminant factors and patterns of the predictors of academic achievement through the decision tree analysis, a data mining method, and examined the relative effects of each factor. Binary logistic regression analysis was performed for viewing. As a result, the most important factor for predicting academic achievement was efficacy, and other factors such as motivation, time management, and depression were predictive of academic achievement. The patterns of factors predicting academic achievement were found to be high in efficacy and time management, and high in motivation for learning even if the efficacy was moderate. Low efficacy and learning motivation, and high depression have been shown to decrease academic achievement. Based on these results, the study suggested the efficacy and motivation to improve academic achievement of college students, strengthening time management education, and managing negative emotions.

Prefetching System based on File Access Pattern Applicable to Multimedia Prefetching Scheme (멀티미디어 선반입에 적용 가능한 파일 액세스 패턴 기반의 선반입 시스템)

  • 황보준형;서대화
    • Journal of Korea Multimedia Society
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    • v.4 no.6
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    • pp.489-499
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    • 2001
  • This paper presents the SIC(Size-Interval-Count) prefetching system that can record the file access patterns of applications within a relatively small space of memory based on the repetitiveness of the file access patterns. The SICPS(SIC Prefetching System) is based on knowledge-based prefetching methods which includes high correctness in predicting future accesses of applications. The proposed system then uses the recorded file access patterns, referred to as "SIC access pattern information", to correctly predict the future accesses of the applications. The proposed prefetching system improved the response time by about 40% compared to the general file system and showed remarkable memory efficiency compared to the previously knowledge-based prefetching methods.

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Mobile User Behavior Pattern Analysis by Associated Tree in Web Service Environment

  • Mohbey, Krishna K.;Thakur, G.S.
    • Journal of Information Science Theory and Practice
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    • v.2 no.2
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    • pp.33-47
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    • 2014
  • Mobile devices are the most important equipment for accessing various kinds of services. These services are accessed using wireless signals, the same used for mobile calls. Today mobile services provide a fast and excellent way to access all kinds of information via mobile phones. Mobile service providers are interested to know the access behavior pattern of the users from different locations at different timings. In this paper, we have introduced an associated tree for analyzing user behavior patterns while moving from one location to another. We have used four different parameters, namely user, location, dwell time, and services. These parameters provide stronger frequent accessing patterns by matching joins. These generated patterns are valuable for improving web services, recommending new services, and predicting useful services for individuals or groups of users. In addition, an experimental evaluation has been conducted on simulated data. Finally, performance of the proposed approach has been measured in terms of efficiency and scalability. The proposed approach produces excellent results.

Using an Adaptive Search Tree to Predict User Location

  • Oh, Se-Chang
    • Journal of Information Processing Systems
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    • v.8 no.3
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    • pp.437-444
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    • 2012
  • In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.

DNS of vortex-induced vibrations of a yawed flexible cylinder near a plane boundary

  • Zhang, Zhimeng;Ji, Chunning;Alam, Md. Mahbub;Xu, Dong
    • Wind and Structures
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    • v.30 no.5
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    • pp.465-474
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    • 2020
  • Vortex-induced vibrations of a yawed flexible cylinder near a plane boundary are numerically investigated at a Reynolds number Ren= 500 based on normal component of freestream velocity. Free to oscillate in the in-line and cross-flow directions, the cylinder with an aspect ratio of 25 is pinned-pinned at both ends at a fixed wall-cylinder gap ratio G/D = 0.8, where D is the cylinder diameter. The cylinder yaw angle (α) is varied from 0° to 60° with an increment of 15°. The main focus is given on the influence of α on structural vibrations, flow patterns, hydrodynamic forces, and IP (Independence Principle) validity. The vortex shedding pattern, contingent on α, is parallel at α=0°, negatively-yawed at α ≤ 15° and positively-yawed at α ≥ 30°. In the negatively- and positively-yawed vortex shedding patterns, the inclination direction of the spanwise vortex rows is in the opposite and same directions of α, respectively. Both in-line and cross-flow vibration amplitudes are symmetric to the midspan, regardless of α. The RMS lift coefficient CL,rms exhibits asymmetry along the span when α ≠ 0°, maximum CL,rms occurring on the lower and upper halves of the cylinder for negatively- and positively-yawed vortex shedding patterns, respectively. The IP is well followed in predicting the vibration amplitudes and drag forces for α ≤ 45° while invalid in predicting lift forces for α ≥ 30°. The vortex-shedding frequency and the vibration frequency are well predicted for α = 0° - 60° examined.

Pattern Analysis of Traffic Accident data and Prediction of Victim Injury Severity Using Hybrid Model (교통사고 데이터의 패턴 분석과 Hybrid Model을 이용한 피해자 상해 심각도 예측)

  • Ju, Yeong Ji;Hong, Taek Eun;Shin, Ju Hyun
    • Smart Media Journal
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    • v.5 no.4
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    • pp.75-82
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    • 2016
  • Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.