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Research of Semantic Considered Tree Mining Method for an Intelligent Knowledge-Services Platform

  • Paik, Juryon
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.5
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    • pp.27-36
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    • 2020
  • In this paper, we propose a method to derive valuable but hidden infromation from the data which is the core foundation in the 4th Industrial Revolution to pursue knowledge-based service fusion. The hyper-connected societies characterized by IoT inevitably produce big data, and with the data in order to derive optimal services for trouble situations it is first processed by discovering valuable information. A data-centric IoT platform is a platform to collect, store, manage, and integrate the data from variable devices, which is actually a type of middleware platforms. Its purpose is to provide suitable solutions for challenged problems after processing and analyzing the data, that depends on efficient and accurate algorithms performing the work of data analysis. To this end, we propose specially designed structures to store IoT data without losing the semantics and provide algorithms to discover the useful information with several definitions and proofs to show the soundness.

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.

Fast OVSF Code Generation Method using Multi-Stage Spreading Scheme (다단 확산 방식을 이용한 효율적인 OVSF 코드 생성 기법)

  • Choi Chang soon;Kim Tae hoon;Kim Young lok;Joung Hwa yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.10A
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    • pp.1123-1130
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    • 2004
  • This paper proposes the fast OVSF code generation method using the multi-stage spreading scheme based on the single code indexing scheme. The conventional OVSF indexing scheme based on the code-tree structure uses two numbers as the codeword indices, the layer number and the code number of the corresponding layer. However, the single code index number implicitly includes the information of the spreading factor as well as the code number. Since the binary representation of the single code indices shows the pattern of the codeword, the orthogonality between two different codewords can be determined by comparing their code indices instead of much longer codewords. The above useful property also makes the codeword can be generated directly kom its single code index. In this paper, the multi-stage spreading scheme is applied to generate the long code by spreading two shorter codewords with the appropriate code indices. The proposed fast code generation algorithm is designed for 3GPP UMTS systems and verified by the simulations.

A Fast Tag Prediction Algorithm using Extra Bit in RFID System (RFID 시스템에서 추가 비트를 이용한 빠른 태그 예측 알고리즘)

  • Baek, Deuk-Hwa;Kim, Sung-Soo;Ahn, Kwang-Seon
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.5
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    • pp.255-261
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    • 2008
  • RFID(Radio Frequency IDentification) is a technology that automatically identifies objects containing the electronic tags by using radio frequency. In RFID system, the reader needs the anti collision algorithm for fast identifring all of the tags in the interrogation zone. This Paper proposes the tree based TPAE(Tag Prediction Algorithm using Extra bit) algorithm to arbitrate the tag collision. The proposed algorithm can identify tags without identifring all the bits in the tag ID. The reader uses the extra bit which is added to the tag ID and if there are two collided bits or multiple collided bits, it checks the extra bit and grasps the tag IDs concurrently. In the experiment, the proposed algorithm had about 50% less query iterations than query tree algorithm and binary search algorithm regardless of the number of tags and tag ID lengths.

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A Hierarchical Cluster Tree Based Fast Searching Algorithm for Raman Spectroscopic Identification (계층 클러스터 트리 기반 라만 스펙트럼 식별 고속 검색 알고리즘)

  • Kim, Sun-Keum;Ko, Dae-Young;Park, Jun-Kyu;Park, Aa-Ron;Baek, Sung-June
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.3
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    • pp.562-569
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    • 2019
  • Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

Union and Division using Technique in Fingerprint Recognition Identification System

  • Park, Byung-Jun;Park, Jong-Min;Lee, Jung-Oh
    • Journal of information and communication convergence engineering
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    • v.5 no.2
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    • pp.140-143
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    • 2007
  • Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In matching between On-line and Off-line treatment, the most important thing is which features we are going to use as the standard. Therefore, we have been using "Delta" and "Core" as this standard until now, but there might have been some deficits not to exist in every person when we set them up as the standards. In order to handle the users who do not have those features, we are still using the matching method which enables us to make up of the spanning tree or the triangulation with the relations of the spanned feature. However, there are some overheads of the time on these methods and it is not sure whether they make the correct matching or not. In this paper, introduces a new data structure, called Union and Division, representing binary fingerprint image. Minutiae detecting procedure using Union and Division takes, on the average, 32% of the consuming time taken by a minutiae detecting procedure without using Union and Division.

A New Reference Pixel Prediction for Reversible Data Hiding with Reduced Location Map

  • Chen, Jeanne;Chen, Tung-Shou;Hong, Wien;Horng, Gwoboa;Wu, Han-Yan;Shiu, Chih-Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.1105-1118
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    • 2014
  • In this paper, a new reversible data hiding method based on a dual binary tree of embedding levels is proposed. Four neighborhood pixels in the upper, below, left and right of each pixel are used as reference pixels to estimate local complexity for deciding embeddable and non-embeddable pixels. The proposed method does not need to record pixels that might cause underflow, overflow or unsuitable for embedment. This can reduce the size of location map and release more space for payload. Experimental results show that the proposed method is more effective in increasing payload and improving image quality than some recently proposed methods.

Modeling the Natural Occurrence of Selected Dipterocarp Genera in Sarawak, Borneo

  • Teo, Stephen;Phua, Mui-How
    • Journal of Forest and Environmental Science
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    • v.28 no.3
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    • pp.170-178
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    • 2012
  • Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed.

Efficient Parallel Visualization of Large-scale Finite Element Analysis Data in Distributed Parallel Computing Environment (분산 병렬 계산환경에 적합한 초대형 유한요소 해석 결과의 효율적 병렬 가시화)

  • Kim, Chang-Sik;Song, You-Me;Kim, Ki-Ook;Cho, Jin-Yeon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.32 no.10
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    • pp.38-45
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    • 2004
  • In this paper, a parallel visualization algorithm is proposed for efficient visualization of the massive data generated from large-scale parallel finite element analysis through investigating the characteristics of parallel rendering methods. The proposed parallel visualization algorithm is designed to be highly compatible with the characteristics of domain-wise computation in parallel finite element analysis by using the sort-last-sparse approach. In the proposed algorithm, the binary tree communication pattern is utilized to reduce the network communication time in image composition routine. Several benchmarking tests are carried out by using the developed in-house software, and the performance of the proposed algorithm is investigated.

A cell distribution algorithm of the copy network in ATM multicast switch (ATM 멀티캐스트 스위치에서 복사 네트워크의 셀 분배 알고리즘)

  • Lee, Ok-Jae;Chon, Byoung-Sil
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.8
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    • pp.21-31
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    • 1998
  • In this paper, a new algorithm is proposed which distributes multicast cells in a copy network. The dual copy network is composed of running adder network, distributor, dummy address encoder, and broadcasting network. It is operated lower input address and higher one simultaneously by the distribution algorithm. As a result, for each input has a better equal opportunity of processing, cell delay and hardware complexity are reduced in copy network. Also, for it adopts the broadcasting network from an expansion Banyan network with binary tree and Banyan network, overflow probability is reduced to a half in that network. As a result of computer simulation, the copy network processed by the distribution algorithm is remarkably improved in cell delay of input buffer according to all input loads.

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