• Title/Summary/Keyword: Binary Data

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Nonparametric Estimation of Univariate Binary Regression Function

  • Jung, Shin Ae;Kang, Kee-Hoon
    • International Journal of Advanced Culture Technology
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    • v.10 no.1
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    • pp.236-241
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    • 2022
  • We consider methods of estimating a binary regression function using a nonparametric kernel estimation when there is only one covariate. For this, the Nadaraya-Watson estimation method using single and double bandwidths are used. For choosing a proper smoothing amount, the cross-validation and plug-in methods are compared. In the real data analysis for case study, German credit data and heart disease data are used. We examine whether the nonparametric estimation for binary regression function is successful with the smoothing parameter using the above two approaches, and the performance is compared.

A New Method of Lossless Universal Data Compression (새로운 무손실 유니버셜 데이터 압축 기법)

  • Kim, Sung-Soo;Lee, Hae-Kee
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.3
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    • pp.285-290
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    • 2009
  • In this paper, we propose a new algorithm that improves the lossless data compression rate. The proposed algorithm lessens the redundancy and improves the compression rate evolutionarily around 40 up to 80 percentile depending on the characteristics of binary images used for compression. In order to demonstrate the superiority of the proposed method, the comparison between the proposed method and the LZ78 (LZ77) is demonstrated through experimental results theoretical analysis.

Holographic s forage of random-phase-modulation-added binary amplitude data (랜덤 위상변조가 가미된 이진 진폭 데이터 영상의 홀로그래픽 저장)

  • 오용석;신동학;장주석
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.05a
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    • pp.489-492
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    • 2001
  • We studied a method to use a variable discrete random phase mask in 2-D binary data representation for efficient holographic data storage. The variable phase mask is realized by use of a twisted nematic liquid crystal display.

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A Kernel Approach to Discriminant Analysis for Binary Classification

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.2
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    • pp.83-93
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    • 2001
  • We investigate a kernel approach to discriminant analysis for binary classification as a machine learning point of view. Our view of the kernel approach follows support vector method which is one of the most promising techniques in the area of machine learning. As usual discriminant analysis, the kernel method can discriminate an object most likely belongs to. Moreover, it has some advantage over discriminant analysis such as data compression and computing time.

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Increase of Binary CDMA transmission range by using Clustering technique (Clustering을 통한 Binary CDMA 전송거리 확보)

  • Choi, Hyeon-Seok;Ji, Choong-Won;Kim, Jung-Sun
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.679-682
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    • 2008
  • High interest for the wireless network is going on the research to apply the related technologies in one's real life. Among these wireless network technologies, local area wireless network, Binary CDMA(Code Division Multiple Access), is the method transferring the data by using RF band based on 2.4Ghz. Binary CDMA has longer transmission distance than Bluetooth. Also, it is of benefit to an inexpensive price because the circuit is simple as compared with being similar to the performance of the existing CDMA. Though Binary CDMA has these benefits, one problem is a frequency overlap, and anther problem is to generate the sections with the shorter distance. To solve these problems, We propose the clustering method that can cover wide area.

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Assessment of Reliability when Using Diagnostic Binary Ratios of Polycyclic Aromatic Hydrocarbons in Ambient Air PM10

  • Pongpiachan, Siwatt
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.18
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    • pp.8605-8611
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    • 2016
  • The reliability of using diagnostic binary ratios of particulate carcinogenic polycyclic aromatic hydrocarbons (PAHs) as chemical tracers for source characterisation was assessed by collecting PM10 samples from various air quality observatory sites in Thailand. The major objectives of this research were to evaluate the effects of day and night on the alterations of six different PAH diagnostic binary ratios: An/(An + Phe), Fluo/(Fluo + Pyr), B[a]A/(B[a]A + Chry), B[a]P/(B[a]P + B[e]P), Ind/(Ind + B[g,h,i]P), and B[k]F/Ind, and to investigate the impacts of site-specific conditions on the alterations of PAH diagnostic binary ratios by applying the concept of the coefficient of divergence (COD). No significant differences between day and night were found for any of the diagnostic binary ratios of PAHs, which indicates that the photodecomposition process is of minor importance in terms of PAH reduction. Interestingly, comparatively high values of COD for An/(An + Phe) in PM10 collected from sites with heavy traffic and in residential zones underline the influence of heterogeneous reactions triggered by oxidising gaseous species from vehicular exhausts. Therefore, special attention must be paid when interpreting the data of these diagnostic binary ratios, particularly for cases of low-molecular-weight PAHs.

Interval prediction on the sum of binary random variables indexed by a graph

  • Park, Seongoh;Hahn, Kyu S.;Lim, Johan;Son, Won
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.261-272
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    • 2019
  • In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

A Study on Decision Tree for Multiple Binary Responses

  • Lee, Seong-Keon
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.971-980
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    • 2003
  • The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.

Implementation of Wireless Distribution Automation System using Binary CDMA Technology (바이너리 CDMA 기술을 이용한 무선 배전 자동화 시스템의 구현)

  • Kwon, Tai-Kil;Cho, Jin-Woong;Hong, Dae-Ki
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.61 no.4
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    • pp.239-244
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    • 2012
  • In this paper, we first introduce our own binary CDMA technology. Then we propose a wireless distribution automation system using the binary CDMA technology. The major research items are the binary CDMA distribution automation system, piconet configuration for remote control and monitoring, scheduling for the transmission and reception of data, and ways of applying encryption to protect wireless packet. To verify the possibility of applying wireless transmission to the distribution automation system, we experiment the implemented system in terms of the transmission rate by applying it to a real-world environment.

Multi-Symbol Binary Arithmetic Coding Algorithm for Improving Throughput in Hardware Implementation

  • Kim, Jin-Sung;Kim, Eung Sup;Lee, Kyujoong
    • Journal of Multimedia Information System
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    • v.5 no.4
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    • pp.273-276
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    • 2018
  • In video compression standards, the entropy coding is essential to the high performance compression because redundancy of data symbols is removed. Binary arithmetic coding is one of high performance entropy coding methods. However, the dependency between consecutive binary symbols prevents improving the throughput. For the throughput enhancement, a new probability model is proposed for encoding multi-symbols at one time. In the proposed method, multi-symbol encoder is implemented with only adders and shifters, and the multiplication table for interval subdivision of binary arithmetic coding is removed. Compared to the compression ratio of CABAC of H.264/AVC, the performance degradation on average is only 1.4% which is negligible.