• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.2
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• pp.297-304
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• 2015

Zeus is one of the will-published malwares. Generally, it infects PC by executing a specific binary file downloaded on the internet. When infected, try to hook a particular Windows API of the currently running processes. If process runs hooked API, this API executes a particular code of Zeus and your private information is leaked. This paper describes techniques to detect and hook Windows API. We believe the technique should be able to detect modern P2P Zeus.

• Journal of Applied and Pure Mathematics
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• v.5 no.3_4
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• pp.187-196
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• 2023

This study is about spin half add operations in 𝓑₂ and 𝓑₃. The burden of technological structures has increased due to the increase in the use of today's technological applications or the processes in the digital systems used. This has increased the importance of fast transactions and storage areas. For this, less transactions, more gain and storage space are foreseen. We have handle tit (triple digit) system instead of bit (binary digit). 729 is reached in 3⁶ in 𝓑₃ while 256 is reached with 2⁸ in 𝓑₂. The volume and number of transactions are shortened in 𝓑₃. The limited storage space at the maximum level is storaged. The logic connectors and the complement of an element in 𝓑₂ and the course of the connectors and the complements of the elements in 𝓑₃ are examined. "Carry" calculations in calculating addition and "borrow" in calculating difference are given in 𝓑₃. The logic structure 𝓑₂ is seen to embedded in the logic structure 𝓑₃. This situation enriches the logic structure. Some theorems and lemmas and properties in logic structure 𝓑₂ are extended to logic structure 𝓑₃.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.7-14
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• 2023

Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people's life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing 'heavy snow' in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.540-542
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• 2023

Due to the serious issues posed by facial manipulation technologies, many researchers are becoming increasingly interested in the identification of face forgeries. The majority of existing face forgery detection methods leverage powerful data adaptation ability of neural network to derive distinguishing traits. These deep learning-based detection methods frequently treat the detection of fake faces as a binary classification problem and employ softmax loss to track CNN network training. However, acquired traits observed by softmax loss are insufficient for discriminating. To get over these limitations, in this study, we introduce a novel discriminative feature learning based on Vision Transformer architecture. Additionally, a separation-center loss is created to simply compress intra-class variation of original faces while enhancing inter-class differences in the embedding space.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.842-857
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• 2023

Currently, most sentiment classification models on microblogging platforms analyze sentence parts of speech and emoticons without comprehending users' emotional inclinations and grasping moral nuances. This study proposes a hybrid sentiment analysis model. Given the distinct nature of microblog comments, the model employs a combined stop-word list and word2vec for word vectorization. To mitigate local information loss, the TextCNN model, devoid of pooling layers, is employed for local feature extraction, while BiLSTM is utilized for contextual feature extraction in deep learning. Subsequently, microblog comment sentiments are categorized using a classification layer. Given the binary classification task at the output layer and the numerous hidden layers within BiLSTM, the Tanh activation function is adopted in this model. Experimental findings demonstrate that the enhanced TextCNN-BiLSTM model attains a precision of 94.75%. This represents a 1.21%, 1.25%, and 1.25% enhancement in precision, recall, and F1 values, respectively, in comparison to the individual deep learning models TextCNN. Furthermore, it outperforms BiLSTM by 0.78%, 0.9%, and 0.9% in precision, recall, and F1 values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1186-1207
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• 2024

Bearings are one of the main components of mechanical equipment and one of the primary components prone to faults. Therefore, conducting fault diagnosis on bearings is a key issue in mechanical equipment research. Belief rule base (BRB) is essentially an expert system that effectively integrates qualitative and quantitative information, demonstrating excellent performance in fault diagnosis. However, class imbalance often occurs in the diagnosis task, which poses challenges to the diagnosis. Models with interpretability can enhance decision-makers' trust in the output results. However, the randomness in the optimization process can undermine interpretability, thereby reducing the level of trustworthiness in the results. Therefore, a hierarchical BRB model based on extreme gradient boosting (XGBoost) feature selection with interpretability (HFS-IBRB) is proposed in this paper. Utilizing a main BRB alongside multiple sub-BRBs allows for the conversion of a multi-classification challenge into several distinct binary classification tasks, thereby leading to enhanced accuracy. By incorporating interpretability constraints into the model, interpretability is effectively ensured. Finally, the case study of the actual dataset of bearing fault diagnosis demonstrates the ability of the HFS-IBRB model to perform accurate and interpretable diagnosis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.518-520
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• 2012

In this paper, based on XML for Logistics EDI system is introduced. XML-based EDI system for the conversion to electronic documents without using a script file, reads and writes to the binary form of the electronic document when the document scanner has been designed and implemented for use with the mappers. In addition, the conversion rules between electronic mapping tool for graphical representation has been designed and implemented. Therefore, the proposed XML-based EDI system for Logistics XML, with a particular vertex of the existing EDI electronic document processing systems and compared to the improvement of user friendliness and speed, portability between other systems filter out nicotine and tar and absorb moisture B2B Gateway system will be used widely.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.101-107
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• 2007

In this paper, we proposed an stable optical security system using interferometer and cascaded phase keys. For the encryption process, a BPCGH(binary phase computer generated hologram) that reconstructs the origial image is designed, using an iterative algorithm and the resulting hologram is regarded as the image to be encrypted. The BPCGH is encrypted through the exclusive-OR operation with the random generated phase key image. For the decryption process, we cascade the encrypted image and phase key image and interfere with reference wave. Then decrypted hologram image is transformed into phase information. Finally, the origianl image is recovered by an inverse Fourier transformation of the phase information. During this process, interference intensity is very sensitive to external vibrations. a stable interference pattern is obtained using self-pumped phase-conjugate minor made of the photorefractive material. In the proposed security system, without a random generated key image, the original image can not be recovered. And we recover another hologram pattern according to the key images, so can be used an authorized system.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.538-542
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• 2001

DNA computing has been applied to the problem of getting an optimal soluting since Adleman's experiment. DNA computing uses strings with various length and four-type bases that makes more useful for finding a global optimal solutions of the complex multi-modal problems This paper presents DNA coding method finding optimal solution of the multi-modal function and compares the efficiency of this method with the genetic algorithms(GA). GA searches efffectively an optimal solution via the artificial evolution of individual group of binary string and DNA coding method uses DNA molecules and four-type bases denoted by the A(Ademine) C(Gytosine);G(Guanine)and T(Thymine). The selection, crossover, mutation operators are applied to both DNA coding algorithm and genetic algorithms and the comparison has been performed. The results show that the DNA based algorithm performs better than GA.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.208-220
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• 2006

Energy of wheeled mobile robot is usually supplied by batteries. In order to extend operation time of mobile robots, it is necessary to minimize the energy consumption. The energy is dissipated mostly in the motors, which strongly depends on the velocity profile. This paper investigates various 3-step (acceleration - cruise - deceleration) speed control methods to minimize a new energy object function which considers the practical energy consumption dissipated in motors related to motor control input, velocity profile, and motor dynamics. We performed an analysis on the energy consumption various velocity profile patterns generated by standard control input such as step input, ramp input, parabolic input, and exponential input. Based on these standard control inputs, we analyzed the six 3-step velocity profile patterns: E-C-E, P-C-P, R-C-R, S-C-S, R-C-S, and S-C-R (S means a step control input, R means a ramp control input, P means a parabolic control input, and E means an exponential control input, C means a constant cruise velocity), and suggested an efficient iterative search algorithm with binary search which can find the numerical solution quickly. We performed various computer simulations to show the performance of the energy-optimal 3-step speed control in comparison with a conventional 3-step speed control with a reasonable constant acceleration as a benchmark. Simulation results show that the E-C-E is the most energy efficient 3-step velocity profile pattern, which enables wheeled mobile robot to extend working time up to 50%.