• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.69-75
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• 2013

To increase the efficiency of the photovoltaic, almost photovoltaic appliances are controlled by Maximum Power Point Tracking(MPPT). Existing most of the PV MPPT techniques have used power which multiplies sensed output current and voltage of the solar cell. However, these algorithms are unnecessarily complicated and too expensive for small and compact system. The other hand, the proposed MPPT technique is only one sensing of the MPPT converter's output current, so there is no need to insert another sensors of battery side. Therefore, this algorithm is simpler compared to the traditional approach and is suitable for low power solar system. Further, the novel proper charge/discharge algorithm for the battery with PV MPPT is developed. In this algorithm, there is CC battery charge mode and load discharge mode of the PV cell & battery dual. Also we design current control to regulate allowable current during the battery charging. The proposed algorithm will be applicable to battery included solar cell applications like solar lantern and solar remote control car. Finally, the proposed method has been verified with computer simulation.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.1-9
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• 2023

Malware files containing concealed malicious scripts have recently been identified within MS Office documents frequently. In response, this paper describes the design and implementation of a system that automatically detects malicious digital files using machine learning techniques. The system is proficient in identifying malicious scripts within MS Office files that exploit the OLE VBA macro functionality, detecting malicious scripts embedded within the CDH/LFH/ECDR internal field values through OOXML structure analysis, and recognizing abnormal CDH/LFH information introduced within the OOXML structure, which is not conventionally referenced. Furthermore, this paper presents a mechanism for utilizing the VirusTotal malicious script detection feature to autonomously determine instances of malicious tampering within MS Office files. This leads to the design and implementation of a machine learning-based integrated software. Experimental results confirm the software's capacity to autonomously assess MS Office file's integrity and provide enhanced detection performance for arbitrary MS Office files when employing the optimal machine learning model.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.67-77
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• 2016

In this paper, we propose an algorithm for open/closed eye detection based on modified Hausdorff distance. The proposed algorithm consists of two parts, face detection and open/closed eye detection parts. To detect faces in an image, MCT (Modified Census Transform) is employed based on characteristics of the local structure which uses relative pixel values in the area with fixed size. Then, the coordinates of eyes are found and open/closed eyes are detected using MHD (Modified Hausdorff Distance) in the detected face region. Firstly, face detection process creates an MCT image in terms of various face images and extract criteria features by PCA(Principle Component Analysis) on offline. After extraction of criteria features, it detects a face region via the process which compares features newly extracted from the input face image and criteria features by using Euclidean distance. Afterward, the process finds out the coordinates of eyes and detects open/closed eye using template matching based on MHD in each eye region. In performance evaluation, the proposed algorithm achieved 94.04% accuracy in average for open/closed eye detection in terms of test video sequences of gray scale with 30FPS/$320{\times}180$ resolution.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.129-135
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• 2019

Recently, studies have been conducted to improve the m-commerce process in the NFC-based mobile environment and the increase of the number of smart phones built in NFC. Since authentication is important in mobile electronic payment, FIDO(Fast IDentity Online) and 2 Factor electronic payment system are applied. In addition, block-chains using distributed raw materials have emerged as a representative technology of the fourth industry. In this study, for the mobile gallery auction of the traders using NFC embedded terminal (smartphone) in a small gallery auction in which an unspecified minority participates, password-based authentication and biometric authentication technology (fingerprint) were applied to record transaction details and ownership transfer of the auction participants in electronic payment. And, for the cost reduction and data integrity related to gallery auction, the private distributed director block chain was constructed and used. In addition, domestic and foreign cases applying block chain in the auction field were investigated and compared. In the future, the study will also study the implementation of block chain networks and smart contract and the integration of block chain and artificial intelligence to apply the proposed method.