• Title/Summary/Keyword: information science high school

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Analysis of high school students' views on science-technology-society (HS-VOSTS) questionnaire results (고등학생을 위한 과학-기술-사회에 대한 시각 (HS-VOST) 설문조사 결과 분석)

  • Kang, Dae-Ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.201-203
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    • 2011
  • We report an experimental result of applying a data mining algorithm for analyzing the questionnaire results of high school students' views on science-technology-society (HS-VOSTS). The preliminary empirical result of Naive Bayes classifier on HS-VOSTS questionnaire from one South Korean university students indicates that data mining algorithms can be effectively applied to automated knowledge discovery from students' survey data.

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A Study on the Effect of Discussion-centered Reading Education on High School Students' Personality & Sociality (토론 중심의 독서교육이 인문계 고등학생의 인성과 사회성 발달에 미치는 영향에 관한 연구)

  • Kim, Gyuwon;Cho, Mi-Ah
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.25 no.2
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    • pp.207-228
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    • 2014
  • This study aims to present the effects of discussion-centered reading education on high school students' personality & sociality using omnidirectional reading-discussion programs. To this end, we adopt an experimental research design with pre/post-test on personality and sociality using the program with the first and second grades high school students located in Chungju City as participants. The results show that the discussion-centered reading education has significant effects on the personality and sociality of high-school students.

Arduino-based power control system implemented by the MyndPlay (MyndPlay를 이용한 Arduino기반의 전원제어시스템 구현)

  • Kim, Byeongsu;Kim, Seungjin;Kim, Taehyung;Baek, Dongin;Shin, Jaehwan;An, Jeong-Eun;Jeong, Deok-Gil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.924-926
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    • 2015
  • In this paper, we use the interface, which many countries concentrates research of Brain - Computer Interface with the device and MyndPlay based on the IoT intelligent Arduino. Finally we will make the Brain - Computer Connection environment, the purpose of Brain - Computer Interface. Recognizes the EEG of a person who wearing the equipment, analyze, classify, and we did a research to design an intelligent thing to suit user's condition. In addition, we use the XBee, and Bluetooth to communicate to other devices, such as smart phone. In conclusion, this paper check users current status via brain waves, and it allows to control the power and other objects by using the EEG(Electroencephalography).

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Traffic Engineering with Segment Routing under Uncertain Failures

  • Zheng, Zengwei;Zhao, Chenwei;Zhang, Jianwei;Cai, Jianping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2589-2609
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    • 2021
  • Segment routing (SR) is a highly implementable approach for traffic engineering (TE) with high flexibility, high scalability, and high stability, which can be established upon existing network infrastructure. Thus, when a network failure occurs, it can leverage the existing rerouting methods, such as rerouting based on Interior Gateway Protocol (IGP) and fast rerouting with loop-free alternates. To better exploit these features, we propose a high-performance and easy-to-deploy method SRUF (Segment Routing under Uncertain Failures). The method is inspired by the Value-at-Risk (VaR) theory in finance. Just as each investment risk is considered in financial investment, SRUF also considers each traffic distribution scheme's risk when forwarding traffic to achieve optimal traffic distribution. Specifically, SRUF takes into account that every link may fail and therefore has inherent robustness and high availability. Also, SRUF considers that a single link failure is a low-probability event; hence it can achieve high performance. We perform experiments on real topologies to validate the flexibility, high-availability, and load balancing of SRUF. The results show that when given an availability requirement, SRUF has greater load balancing performance under uncertain failures and that when given a demand requirement, SRUF can achieve higher availability.

A Comparison of Students Satisfaction with School Foodservice Program by Foodservice Operation Types in Middle and High Schools Students in the Geumsan-Gun Area (급식 운영 형태에 따른 금산 지역 중.고등학생의 학교 급식 만족도)

  • Kim, Sung-Hwan;Kim, Na-Young;Lee, Kyung-Hwa
    • Journal of the East Asian Society of Dietary Life
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    • v.17 no.4
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    • pp.597-606
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    • 2007
  • The purpose of this study was to investigate the satisfaction with school foodservice programs by foodservice operation type in middle school and high school students in the Geumsan-Gun area. A total of 530 subjects(250 middle school and 280 high school students) from the Geumsan-Gun area participated from March 15 to March 23, 2004. Questionnaires were used to study dietary habits, activity levels, and current health conditions. The results of the study are summarized as follows. Based on the body mass index(BMI) scores of the students, the high school male BMI scores were significantly different(5%), and they were underweight for their height. The students were primarily dissatisfied with times for meals for school foodservice under direct management and with the quantity of meal for school foodservice under contract. Compared to the middle school female students, the male high school students were dissatisfied with the time for meals and quantity of food. Generally, the students were satisfied with dessert items the most. The food most often wasted was soup. The middle and high school students preferred food services to those under contract.

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Turbulence-tolerant Manchester On-off Keying Transmission for Free-space Optical Communication

  • Qian-Wen Jing;Pei-Zheng Yu;Han-Lin Lv;Yanqing Hong
    • Current Optics and Photonics
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    • v.7 no.4
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    • pp.345-353
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    • 2023
  • We propose a turbulence-tolerant Manchester on-off keying (M-OOK) transmission for free-space optical (FSO) communication. At the transmitter end, a M-OOK signal featuring a spectrum with low-frequency components absent is modulated and transmitted into a turbulent channel. At the receiver end, a low-pass filter (LPF) -based adaptive-threshold decision (ATD) with LPF-extracted channel-state information (CSI) and a high-pass filter (HPF)-based fixed-threshold decision (FTD) are employed to compensate for the effects of turbulence, owing to the low-frequency spectral characteristics of the turbulent channel. The performance of LPF-based ATD and HPF-based FTD are evaluated for various cutoff frequencies for the LPF and HPF. Besides, the proposed M-OOK transmission is compared to conventional non-return-to-zero OOK (NRZ-OOK) for different data rates. The proposed technique is verified in simulation. The simulation results show that the proposed M-OOK detection with optimized cutoff frequencies of LPF and HPF has better bit-error-rate (BER) performance compared to NRZ-OOK, and it is close to the theoretical ATD with the knowledge of precise CSI under various degrees of turbulence effects.

Multiple Network-on-Chip Model for High Performance Neural Network

  • Dong, Yiping;Li, Ce;Lin, Zhen;Watanabe, Takahiro
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.10 no.1
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    • pp.28-36
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    • 2010
  • Hardware implementation methods for Artificial Neural Network (ANN) have been researched for a long time to achieve high performance. We have proposed a Network on Chip (NoC) for ANN, and this architecture can reduce communication load and increase performance when an implemented ANN is small. In this paper, a multiple NoC models are proposed for ANN, which can implement both a small size ANN and a large size one. The simulation result shows that the proposed multiple NoC models can reduce communication load, increase system performance of connection-per-second (CPS), and reduce system running time compared with the existing hardware ANN. Furthermore, this architecture is reconfigurable and reparable. It can be used to implement different applications of ANN.

Depth Up-Sampling via Pixel-Classifying and Joint Bilateral Filtering

  • Ren, Yannan;Liu, Ju;Yuan, Hui;Xiao, Yifan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3217-3238
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    • 2018
  • In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

A Text Similarity Measurement Method Based on Singular Value Decomposition and Semantic Relevance

  • Li, Xu;Yao, Chunlong;Fan, Fenglong;Yu, Xiaoqiang
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.863-875
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    • 2017
  • The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

Multi-view Clustering by Spectral Structure Fusion and Novel Low-rank Approximation

  • Long, Yin;Liu, Xiaobo;Murphy, Simon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.813-829
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    • 2022
  • In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.