• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.185-193
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• 2019

In this paper, we propose the effects of programming-based TPACK educational program on the pre-service teacher's self-efficacy beliefs for technology integration. For this study, pre-service teachers who received programming education and TPACK education based on ICT were set as control group and pre-service teachers who received programming-based TPACK education as experimental group. In order to observe the change, the pre-service teachers conducted the test tool to measure the self-efficacy beliefs for technology integration before and after applying the educational program. As a result of the study, only the pre-service teachers who received the programming-based TPACK education showed significant improvement in the self-efficacy beliefs for technology integration. Furthermore, in the post-test, the experimental group showed a significantly higher difference than the control group. Through this study, it was concluded that programming-based TPACK educational program is effective in enhancing pre-service teacher's self-efficacy beliefs for technology integration.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.10-12
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• 2003

Recommender systems help consumers to find the useful products from the overloaded information. Researchers have developed content-based recommenders, collaborative recommenders, and a few hybrid systems. In this research, we extend the classic collaborative recommenders by clustering method to form a hybrid recommender system. Using the clustering method, we can recommend the products based on not only the user ratings but also other useful information from user profiles or attributes of items. Through our experiments on well-known MovieLens data set, we found that the information provided by the attributes of item on the item-based collaborative filter shows advantage over the information provided by user profiles on the user-based collaborative filter.

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1383-1394
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• 2016

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1246-1259
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• 2015

Certificate-based signature (CBS) combines the advantages of both public key-based signature and identity-based signature, while saving from the disadvantages of drawbacks in both PKS and IBS. The insecure deployment of CBS under the hostile circumstances usually causes the exposure of signing key to be inescapable. To resist the threat of key leakage, we present a pairing-free key insulated CBS scheme by incorporating the idea of key insulated mechanism and CBS. Our scheme eliminates the costly pairing operations and as a matter of fact outperforms the existing key insulated CBS schemes. It is more suitable for low-power devices. Furthermore, the unforgeability of our scheme has been formally proven to rest on the discrete logarithm assumption in the random oracle model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5574-5591
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• 2017

Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.37-43
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• 2015

In this paper, a new background subtraction algorithm for video based fence monitoring surveillance systems is proposed. We adopt the sampling based background subtraction technique and focus on the two main issues: handling highly dynamic environment and handling the flickering nature of pulse based IR (infrared) lamp. Natural scenes from fence monitoring system are usually composed of several dynamic entities such as swaying trees, moving water, waves and rain. To deal with such dynamic backgrounds, we utilize the confidence factor for each background value of the input image. For the flickering IR lamp, the original sampling based technique is extended to handle double background models. Experimental results revealed that our method works well in real fence monitoring surveillance systems.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.124-128
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• 2024

Cloud computing is a technology for delivering information in which resources are retrieved from the internet through a web-based tools and applications, rather than a direct connection with the server. It is a new emerging computing based technology in which any individual or organization can remotely store or access the information. The structure of cloud computing allows to store and access various information as long as an electronic device has access to the web. Even though various merits are provided by the cloud from the cloud provides to cloud users, it suffers from various flaws in security. Due to these flaws, data integrity and confidentiality has become a challenging task for both the storage and retrieval process. This paper proposes a novel approach for data protection by an improved auditing based methodology in cloud computing especially in the process of cloud storage. The proposed methodology is proved to be more efficient in auditing the threats while storing data in the cloud computing architecture.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.231-240
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• 2007

This paper presents an advanced modeling and simulation technique applied to DC/DC power electronic converters fed through renewable energy power sources. The distributed generation (DG) system at the Illinois Institute of Technology, which employs a phase-l system consisting of a photovoltaic-based power system and a phase-2 system consisting of a fuel cell based primary power source, is studied. The modeling and simulation of the DG system is done using the generalized state space averaging (GSSA) method. Furthermore, the paper compares the results achieved upon simulation of the specific GSSA models with those of popular computer aided design software simulations performed on the same system. Finally, the GSSA and CAD software simulation results are accompanied with test results achieved via experimentation on both, the PV-based phase-l system and the fuel cell based phase-2 power system.

• Current Optics and Photonics
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• v.8 no.3
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.415-421
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• 2007

This paper proposes a convolution tree kernel-based approach for relation extraction where the parse tree is expanded with entity features such as entity type, subtype, and mention level etc. Our study indicates that not only can our method effectively capture both syntactic structure and entity information of relation instances, but also can avoid the difficulty with tuning the parameters in composite kernels. We also demonstrate that predicate verb information can be used to further improve the performance, though its enhancement is limited. Evaluation on the ACE2004 benchmark corpus shows that our system slightly outperforms both the previous best-reported feature-based and kernel-based systems.