• Title/Summary/Keyword: selectivity estimation

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Performance Improvement of Declustering Algorithm by Efficient Grid-Partitioning Multi-Dimensional Space (다차원 공간의 효율적인 그리드 분할을 통한 디클러스터링 알고리즘 성능향상 기법)

  • Kim, Hak-Cheol
    • Journal of Korea Spatial Information System Society
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    • v.12 no.1
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    • pp.37-48
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    • 2010
  • In this paper, we analyze the shortcomings of the previous declustering methods, which are based on grid-like partitioning and a mapping function from a cell to a disk number, for high-dimensional space and propose a solution. The problems arise from the fact that the number of splitting is small(for the most part, binary-partitioning is sufficient), and the side length of a range query whose selectivity is small is quite large. To solve this problem, we propose a mathematical model to estimate the performance of a grid-like partitioning method. With the proposed estimation model, we can choose a good grid-like partitioning method among the possible schemes and this results in overall improvement in declustering performance. Several experimental results show that we can improve the performance of a previous declustering method up to 2.7 times.

Science & Engineering Degrees and Human Resource Element Value Estimation in Technology Jobs : the US Case (기술직에서 이공계학위와 인적자원요소의 가치평가 : 미국사례)

  • Lee, Sae Jae;Lee, Hyun Soo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.221-229
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    • 2017
  • In the international businesses human resource elements acquired in different countries might have different values in varied industries due to the different quality of education and experiences in the original countries. Using selection models to evaluate expected values in earnings equation of human resource elements such as education and experiences etc. acquired in sending countries, system equations are expanded to examine also the values of science and engineering degrees in technology jobs with selectivity bias correction. This paper used the US census survey data of 2015 on earnings, academic degrees, occupations etc. The US has long maintained the policy of accepting more STEM workers than any other countries and helped maintaining own technological leadership. Assuming per capita GDP gap between the sending country and the US downgrades immigrant human resource quality, it rarely affects occupational selection but depresses earnings on average by two or more years' worth of education. Immigrant quality index in the sense of GDP gap appears to be a valid tool to assess the expected earnings of the worker with. Engineering degrees increase significantly the probability of selecting not only engineering jobs but also general management jobs, as well as increasing the expected earning additionally over nine years'worth of education. Getting a technology job is additionally worth about four years of education. Economics and business degrees are worth additionally almost six years of education but humanities degrees depress expected earnings. Since years after immigration does not very fast enhance earnings capacity, education level and English language ability might be more useful criteria to expect better future earnings by.

A Preliminary Study on Evaluation of TimeDependent Radionuclide Removal Performance Using Artificial Intelligence for Biological Adsorbents

  • Janghee Lee;Seungsoo Jang;Min-Jae Lee;Woo-Sung Cho;Joo Yeon Kim;Sangsoo Han;Sung Gyun Shin;Sun Young Lee;Dae Hyuk Jang;Miyong Yun;Song Hyun Kim
    • Journal of Radiation Protection and Research
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    • v.48 no.4
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    • pp.175-183
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    • 2023
  • Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste. Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column. Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R2 score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times. Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

인터넷 질의 처리를 위한 웨이블릿 변환에 기반한 통합 요약정보의 관리

  • Joe, Moon-Jeung;Whang, Kyu-Young;Kim, Sang-Wook;Shim, Kyu-Seok
    • Journal of KIISE:Databases
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    • v.28 no.4
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    • pp.702-714
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    • 2001
  • As Internet technology evolves, there is growing need of Internet queries involving multiple information sources. Efficient processing of such queries necessitates the integrated summary data that compactly represents the data distribution of the entire database scattered over many information sources. This paper presents an efficient method of managing the integrated summary data based on the wavelet transform and addresses Internet query processing using the integrated summary data. The simplest method for creating the integrated summary data would be to summarize the integrated data sidtribution obtained by merging the data distributions in multiple information sources. However, this method suffers from the high cost of transmitting storing and merging a large amount of data distribution. To overcome the drawbacks, we propose a new wavelet transform based method that creates the integrated summary data by merging multiple summary data and effective method for optimizing Internet queries using it A wavelet transformed summary data is converted to satisfy conditions for merging. Moreover i the merging process is very simpe owing to the properties of the wavelet transform. we formally derive the upper bound of the error of the wavelet transformed intergrated summary data. Compared with the histogram-based integrated summary data the wavelet transformedintegrated summary data provesto be 1.6~5.5 time more accurate when used for selectivity estimation in experiments. In processing Internet top-N queries involving 56 information sources using the integrated summary data reduces the processing cost to 1/44 of the cost of not using it.

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