• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.197-202
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• 2022

IoT (Internet of Things) devices are being attacked by malware due to many security vulnerabilities, such as the use of weak IDs/passwords and unauthenticated firmware updates. However, due to the diversity of CPU architectures, it is difficult to set up a malware analysis environment and design features. In this paper, we design time series features using the byte sequence of executable files to represent independent features of CPU architectures, and analyze them using recurrent neural networks. The proposed feature is a fixed-length time series pattern extracted from the byte sequence by calculating partial entropy and applying linear interpolation. Temporary changes in the extracted feature are analyzed by RNN and LSTM. In the experiment, the IoT malware detection showed high performance, while low performance was analyzed in the malware family classification. When the entropy patterns for each malware family were compared visually, the Tsunami and Gafgyt families showed similar patterns, resulting in low performance. LSTM is more suitable than RNN for learning temporal changes in the proposed malware features.

• Journal of Powder Materials
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• v.30 no.1
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• pp.1-6
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• 2023

High-entropy alloys (HEAs) are attracting attention because of their excellent properties and functions; however, they are relatively expensive compared with commercial alloys. Therefore, various efforts have been made to reduce the cost of raw materials. In this study, MIM is attempted using coarse equiatomic CoCrFeMnNi HEA powders. The mixing ratio (powder:binder) for HEA feedstock preparation is explored using torque rheometer. The block-shaped green parts are fabricated through a metal injection molding process using feedstock. The thermal debinding conditions are explored by thermogravimetric analysis, and solvent and thermal debinding are performed. It is densified under various sintering conditions considering the melting point of the HEA. The final product, which contains a small amount of non-FCC phase, is manufactured at a sintering temperature of 1250℃.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.101-111
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• 2015

Stream restoration projects have become threats to riparian ecosystem in Rep. of korea. Riparian wildlife becomes isolated and the animals are often experience difficulties in crossing riparian corridors. The purposes of this study is to select suitable wildlife passages for wild animals crossing riparian corridors. Maximum entropy model and snow tracking data on embankment in winter seasons were used to develop species distribution models to select suitable wildlife passages for water deer. The analysis suggests the following. Firstly, most significant factors for water deer's habitat in area nearby riparian area are shown to distance to water, age-class, land cover, slope, aspect, digital elevation model, tree density, and distance to road. For the riparian area, significant factors are shown to be land cover, size of riparian area, distance to tributary, and distance to built-up. Secondly, the suitable wildlife passages are recommended to reflect areas of high suitability with Maximum Entropy model in riparian areas and the surrounding areas and moving passages. The selected suitable areas are shown to be areas with low connectivity due to roads and vertical levee although typical habitats for water deer are forest, grassland, and farmland. In addition, the analysis of traces on snow suggests that the water deer make a detour around the artificial structures. In addition, the water deer are shown to make a detour around the fences of roads and embankment around farmland. Lastly, the water deer prefer habitats around riparian areas following tributaries. The method used in this study is expected to provide cost-efficient and functional analysis in selecting suitable areas.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.5
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• pp.83-93
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• 2017

This study proposed the new weighting values and fault points of condition assessment items for reinforced earth retaining walls based on the combination the inspection data and hybrid weighting technique. Utilizing the inspection data of 161 reinforced earth retaining walls, multi regression analysis and entropy technique were applied to gain the weighting values of condition assessment items. In addition, the weighting values by AHP technique was analyzed based on the opinion of experts. By appling hybrid weighting technique to the calculated weighting values obtained by the individual technique, the new weighting values of condition assessment items were proposed, and the fault points and fault indices of reinforced earth retaining walls were proposed. Results showed that the rank of the weighting value of the condition evaluation items was fluctuated according to the multiple regression analysis, AHP technique, and entropy technique. There was no duplication of the rank of the weighting value while the current weighting value was overlapped. Specially, in the rsults of multi regression analysis, two condition assessment items were occupied 70% of the total weights. When the proposed weighting values were applied to existing reinforced earth retaining wall of 161, 16 reinforced earth retaining walls showed the increased risk rank and 31 represented the decreased risk rank.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.7
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• pp.883-889
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• 2013

The distribution of a response usually depends on the distribution of a variable. When the distribution of a variable has two different modes, the response also follows a distribution with two different modes. In most reliability analysis methods, the number of modes is irrelevant, but not the type of distribution. However, in actual problems, because information is often provided with two or more modes, it is important to estimate the distributions with two or more modes. Recently, some reliability analysis methods have been suggested for bimodal distributions. In this paper, we review some methods such as the Akaike information criterion (AIC) and maximum entropy principle (MEP) and compare them with the Monte Carlo simulation (MCS) using mathematical examples with two different modes.

• Clean Technology
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• v.26 no.3
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• pp.168-176
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• 2020

The introduction of the Korea toxics use reduction (TUR) program to build a clean society is generally evaluated based on social economic criteria. Among various techniques, benefit-cost analysis is the most commonly used. This method is focused on the calculation and comparison of all the benefits and costs attributable to the TUR program. However, since it is reasonable to consider not only economic criteria but also policy criteria in the process of evaluation, it is necessary to reflect on the criteria weights found in the benefits and costs. This study aims at developing a new evaluation technique to achieve this purpose and apply it to the Korean TUR program to be implemented in 2020. This study selected competitiveness, toxic substances' emission reduction ratio, and health improvement as policy criteria. The Analytic Hierarchy Process (AHP) technique was initially used to calculate the weight and then, based on the results, the concept of information entropy introduced by Claude Shannon was used to eliminate subjective bias. As a result of the study, it was found that the revised benefit-cost analysis considering the weights of the policy criteria, as well as the existing economic criteria, could be a reasonable alternative in evaluating the feasibility of TUR regulations for highly toxic substances.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.27-34
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• 2006

In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2769-2784
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• 2020

This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities' scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists' online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists' overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists' satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists' overall image of the ancient city.

• Applied Chemistry for Engineering
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• v.17 no.1
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• pp.93-99
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• 2006

Methods to distinguish flow regimes in gas-solid fluidized bed have been investigated by adopting the concept of chaos theory. Pressure fluctuations have been chosen as a state variable for the analysis of the system. Pressure fluctuations obtained from differential pressure transducer have been investigated using the chaos analysis (Correlation dimension and Kolmogorov entropy) as well as the average and standard deviation. As a result, fluidization regimes in gas-solid fluidized bed can be distinguished by statistics methods as the average and standard deviation. Also, Correlation dimension and Kolmogorov entropy could be used to classify the fluidization regimes.