Digital Library

1. 61. A Study on the Structural Equation Modeling for the effect of e-Learning
   Gyun Heo, Vol. 15, No. 6, pp. 77-84, Dec. 2014
   10.7472/jksii.2014.15.6.77
   Keywords: E-learning, Learning Effect, structural equation modeling
2. 62. Context Aware Feature Selection Model for Salient Feature Detection from Mobile Video Devices
   Jaeho Lee, Hyunkyung Shin, Vol. 15, No. 6, pp. 117-124, Dec. 2014
   10.7472/jksii.2014.15.6.117
   Keywords: feature vector selection, nearest neighbor search, Principal Component Analysis, salient feature detection, Machine Learning
3. 63. An Analysis of the Awareness of Undergraduate Students Toward Educational Methods Utilizing SNS
   Mihyun Chung, Yeongrok Gim, Jaehyoun Kim, Vol. 15, No. 5, pp. 33-42, Oct. 2014
   10.7472/jksii.2014.15.5.33
   Keywords: SNS, Social Learning, Student Perspective, qualitative Research
4. 64. Bio-mimetic Recognition of Action Sequence using Unsupervised Learning
   Jin Ok Kim, Vol. 15, No. 4, pp. 9-20, Aug. 2014
   10.7472/jksii.2014.15.4.09
   Keywords: Action sequence detection, Categorical action classification, Bio-inspired Action perception, Unsupervised learning
5. 65. A Study on Educational Application of Smart Devices for Enhancing the Effectiveness of Problem Solving Learning
   Meeyong Kim, Vol. 15, No. 1, pp. 143-156, Feb. 2014
   10.7472/jksii.2014.15.1.143
   Keywords: smart devices, Smart Education, Problem Solving Learning, Teaching.Learning Activity
6. 66. A Study on the Actual Condition and Utilization Plan of Smart Devices for Educational Purpose
   Yeongrok Gim, Mihyun Chung, Jaehyoun Kim, Vol. 14, No. 3, pp. 47-56, Jun. 2013
   10.7472/jksii.2013.14.3.47
   Keywords: smart devices, smart learning, efficacy, class types, courses, teaching-learning process
7. 67. Leveraging Big Data for Spark Deep Learning to Predict Rating
   Monika Mishra, Mingoo Kang, Jongwook Woo, Vol. 21, No. 6, pp. 33-39, Dec. 2020
   10.7472/jksii.2020.21.6.33
   Keywords: Big data, Deep Learning, Spark, Analytics Zoo, Amazon EMR, Machine Learning, Recommendation
8. 68. Random Balance between Monte Carlo and Temporal Difference in off-policy Reinforcement Learning for Less Sample-Complexity
   Chayoung Kim, Seohee Park, Woosik Lee, Vol. 21, No. 5, pp. 1-7, Oct. 2020
   10.7472/jksii.2020.21.5.1
   Keywords: Deep Q-Network, Temporal Difference, Monte Carlo, Reinforcement Learning, Variation and Bias Balance
9. 69. Prediction of infectious diseases using multiple web data and LSTM
   Yeongha Kim, Inhwan Kim, Beakcheol Jang, Vol. 21, No. 5, pp. 139-148, Oct. 2020
   10.7472/jksii.2020.21.5.139
   Keywords: Machine Learning, Predict infectious diseases, Web data, LSTM
10. 70. An LSTM Neural Network Model for Forecasting Daily Peak Electric Load of EV Charging Stations
    Haesung Lee, Byungsung Lee, Hyun Ahn, Vol. 21, No. 5, pp. 119-127, Oct. 2020
    10.7472/jksii.2020.21.5.119
    Keywords: EV, Peak electric load, Load forecasting, Deep Learning, LSTM