• The Journal of the Acoustical Society of Korea
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• v.41 no.1
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• pp.52-57
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• 2022

Speech consists of the sum of complex sine-waves. This study investigated the perception of electrical hearing by applying the sinusoidal model to cochlear implant simulation. Fourteen adults with normal hearing participated in this study. The sentence recognition tests were implemented using the sentence lists processed by the sinusoidal model which extracts 2, 4, 6, 8 sine-wave components and sentence lists processed by the same sinusoidal model along with cochlear implant simulation (8 channel vocoders). The results showed lower speech recognition for the sentence lists processed by the sinusoidal model and cochlear implant simulation compared to those by the sinusoidal model alone. Notably, the lower the number of sine-wave components (2), the larger the difference was. This study provides the perceptual pattern of sine-wave speech for electrical hearing by cochlear implant listeners, and basic data for development of speech processing algorithms in cochlear implants.

• 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 Digital Convergence
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• v.20 no.5
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• pp.593-598
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• 2022

Recently, data production has seen explosive growth, and the storage systems to store these big data safely and quickly is evolving in various ways. A typical configuration of storage systems is the use of SSDs with fast data processing speed as a RAID group that can maintain reliable data. However, since NAND flash memory, which composes SSD, has the feature that deterioration if writes more than a certain number of times are repeated, can increase the likelihood of simultaneous failure on multiple SSDs in a RAID group. And this can result in serious reliability problems that data cannot be recovered. Thus, in order to solve this problem, we propose a method of throttling IOs so that each SSD within a RAID group leads to a different life-end. The technique proposed in this paper utilizes SMART to control the state of each SSD and the number of IOs allocated according to the data pattern used step by step. In addition, this method has the advantage of preventing large amounts of concurrency defects in RAID because it induces differential lifetime finishes of SSDs.

• Journal of the Korean Geotechnical Society
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• v.22 no.7
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• pp.5-12
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• 2006

In this study, 2D shallow tunnel model test using close range photogrammetric technique was conducted with aluminium rods simulating continuum granular material. Numerical analysis was also carried out in order to identify the behaviour of subsurface deformations caused by shallow tunnelling. Direction and magnitude of displacement vectors from the model test were identical to the result of numerical analysis based on the model data. In particular, it is shown that the vector direction was toward a point below the tunnel invert level. A narrow "chimney or tulip like" pattern of vertical displacement was confirmed by both the model test and numerical analysis. This behaviour is consistent with the field data. In addition to the qualitative comparison, the quantitative result of subsurface settlements according to 2D volume loss showed good agreement between the model test and numerical analysis. Therefore, close range photogrammetric technique applied in the model test may be used to validate the result from the continuum numerical analysis.

• Composites Research
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• v.19 no.3
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• pp.23-28
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• 2006

Carbon nanotubes reinforced copper matrix laminated nanocomposites were developed and the mechanical properties were evaluated by using micro-tensile testing system. Sandwich-type laminated structure constituted with carbon nanotube layers as a reinforcement and electroplated copper matrix were fabricated by a new processing approach based on selective dip-coating of carbon nanotubes. The mechanical properties of nanocomposites were improved due to an enhanced load sharing capacity of carbon nanotubes homogeneously distributed within the in-plane direction, as well as a bridging effect of carbon nanotubes along the out-of-plane direction between the upper and lower matrices. The universality of the layering approach is applicable to a wide range of functional materials, and here we demonstrate its potential use in reinforcing composite materials.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.99-106
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• 2009

Though edge detection, an important stage that significantly affecting the performance of image recognition, has been given numerous researches on its execution methods, it still remains as difficult problem and it is one of the components for image recognition applications while it is not the only way to identify an object or track a specific area. This paper, unlike gradient operator using edge detection method, found out edge pixel by referring to 2 neighboring pixels information in binary image and comparing them with pre-defined 4 edge pixels pattern, and detected binary image edge by determining the direction of the next edge detection exploring pixel and proposed method to detect binary image edge by repeating step of edge detection to detect another area edge. When recognizing image, if edge is detected with the use of gradient operator, thinning process, the stage next to edge detection, can be omitted, and with the edge detection algorithm executing time reduced compared with existing area edge tracing method, the entire image recognizing time can be reduced by applying real-time image recognizing system.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.1-6
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• 2023

Morphological analysis is a branch of natural language processing, is now a rapidly growing field. The fundamental tenet of morphological analysis is that it can establish the roots or stems of words and enable comparison to the original term. Arabic is a highly inflected and derivational language and it has a strong structure. Each root or stem can have a large number of affixes attached to it due to the non-concatenative nature of Arabic morphology, increasing the number of possible inflected words that can be created. Accurate verb recognition and extraction are necessary nearly all issues in well-known study topics include Web Search, Information Retrieval, Machine Translation, Question Answering and so forth. in this work we have designed and implemented an algorithm to detect and recognize Arbic Verbs from Arabic text.The suggested technique was created with "Python" and the "pyqt5" visual package, allowing for quick modification and easy addition of new patterns. We employed 17 alternative patterns to represent all verbs in terms of singular, plural, masculine, and feminine pronouns as well as past, present, and imperative verb tenses. All of the verbs that matched these patterns were used when a verb has a root, and the outcomes were reliable. The approach is able to recognize all verbs with the same structure without requiring any alterations to the code or design. The verbs that are not recognized by our method have no antecedents in the Arabic roots. According to our work, the strategy can rapidly and precisely identify verbs with roots, but it cannot be used to identify verbs that are not in the Arabic language. We advise employing a hybrid approach that combines many principles as a result.

• Structural Engineering and Mechanics
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• v.86 no.4
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• pp.473-486
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• 2023

Nowadays, urban centers are increasingly vertical, making architects and engineers look for more efficient tools to analyze the effects of wind on tall buildings. Topology optimization can be used as an efficient tool for the design of bracing systems. Therefore, this work obtained the wind loads that act in the CAARC building, following the Brazilian standard NBR 6123/1988 and using Computational Fluid Dynamics. Four loading situations were considered, using the SIMP and BESO methods to optimize two-dimensional structures. A comparison between the SIMP and BESO methods is presented, showing the differences in the geometry of the solution found by both methods, the percentage variation in the objective function values and the dimensionless processing time. The solutions obtained through the loads obtained by the Brazilian standard are also compared with the numerical solutions obtained by CFD. The results show that the BESO method presented more rigid structures compared to the SIMP method. The bracing structures obtained with the SIMP method always present similar patterns in the distribution and quantity of bars, in contrast to the BESO method where no characteristic topology pattern was observed. It was concluded that even though the structures obtained by the BESO method presented greater stiffness, the SIMP method was less susceptible to the methodology used for the determination of wind loads. Additionally, it was evident the great potential that the combination topology optimization and computational wind engineering have in the design of bracing systems of high functional and aesthetic standards.

• Imaging Science in Dentistry
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• v.53 no.2
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• pp.109-115
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• 2023

Purpose: The aim of this study was to evaluate changes in the trabecular bone through texture analysis and compare the texture analysis characteristics of different areas in patients with medication-related osteonecrosis of the jaw (MRONJ). Materials and Methods: Cone-beam computed tomographic images of 16 patients diagnosed with MRONJ were used. In sagittal images, 3 regions were chosen: active osteonecrosis(AO); intermediate tissue (IT), which presented a zone of apparently healthy tissue adjacent to the AO area; and healthy bone tissue (HT) (control area). Texture analysis was performed evaluating 7 parameters: secondary angular momentum, contrast, correlation, sum of squares, inverse moment of difference, sum of entropies, and entropy. Data were analyzed using the Kruskal-Wallis test with a significance level of 5%. Results: Comparing the areas of AO, IT, and HT, significant differences (P<0.05) were observed. The IT and AO area images showed higher values for parameters such as contrast, entropy, and secondary angular momentum than the HT area, indicating greater disorder in these tissues. Conclusion: Through texture analysis, changes in the bone pattern could be observed in areas of osteonecrosis. The texture analysis demonstrated that areas visually identified and classified as IT still had necrotic tissue, thereby increasing the accuracy of delimiting the real extension of MRONJ.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.835-843
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• 2023

Given the structure of XML data, path and tree pattern matching algorithms play an important role in XML query processing. To facilitate decisions or relationships between nodes, nodes in an XML tree are typically labeled in a way that can quickly establish an ancestor-descendant on relationship between two nodes. However, these techniques have the disadvantage of re-labeling existing nodes or recalculating certain values if insertion occurs due to sequential updates. Therefore, in current labeling techniques, the cost of updating labels is very high. In this paper, we propose a new labeling technique called Fast XML encoding, which supports the update of order-sensitive XML documents without re-labeling or recalculation. It also controls the length of the label by reusing deleted labels at the same location in the XML tree. The proposed reuse algorithm can reduce the length of the label when all deleted labels are inserted in the same location. The proposed technique in the experimental results can efficiently handle order-sensitive queries and updates.