• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.61-66
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• 2009

본 논문은 다양한 형태의 웹 문서에 적용하기 위해서, 언어의 통계정보 및 후처리 규칙에 기반 하여 개선된 문장경계 인식 기술을 제안한다. 제안한 방법은 구두점 생략 및 띄어쓰기 오류가 빈번한 웹 문서에 적용하기 위해서 문장경계로 사용될 수 있는 모든 음절을 대상으로 학습하여 문장경계 인식을 수행하였고, 문장경계인식 성능을 최대화 하기 위해서 다양한 실험을 통해 최적의 자질 및 학습데이터를 선정하였고, 다양한 기계학습 기반 분류 모델을 비교하여 최적의 분류모델을 선택하였으며, 학습데이터에 의존적인 통계모델의 오류를 규칙에 기반 해서 보정하였다. 성능 실험은 다양한 형태의 문서별 성능 측정을 위해서 문어체와 구어체가 복합적으로 사용된 신문기사와 블로그 문서(평가셋1), 문어체 위주로 구성된 세종말뭉치와 백과사전 본문(평가셋2), 구두점 생략 및 띄어쓰기 오류가 빈번한 웹 사이트의 게시판 글(평가셋3)을 대상으로 성능 측정을 하였다. 성능척도로는 F-measure를 사용하였으며, 구두점만을 대상으로 문장경계 인식 성능을 평가한 결과, 평가셋1에서는 96.5%, 평가셋2에서는 99.4%를 보였는데, 구어체의 문장경계인식이 더 어려움을 알 수 있었다. 평가셋1의 경우에도 규칙으로 후처리한 경우 정확률이 92.1%에서 99.4%로 올라갔으며, 이를 통해 후처리 규칙의 필요성을 알 수 있었다. 최종 성능평가로는 구두점만을 대상으로 학습된 기본 엔진과 모든 문장경계후보를 인식하도록 개선된 엔진을 평가셋3을 사용하여 비교 평가하였고, 기본 엔진(61.1%)에 비해서 개선된 엔진이 32.0% 성능 향상이 있음을 확인함으로써 제안한 방법이 웹 문서에 효과적임을 입증하였다.

• Journal of Sensor Science and Technology
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• v.2 no.1
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• pp.19-27
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• 1993

Capacitive pressure sensor for low pressure measurements has been fabricated by using $n^{+}$ epitaxial layer electrochemical etching stop and glass-to-silicon electrostatic bonding technique. The sensor had hybrid configuration of a sensor chip, which consists of sensor capacitor and reference capacitor, and two output signal detection IC chips. A fabricated sensor, with a $1.0{\times}1.0 mm^{2}$ square size and a $10{\mu}m$ thick flat diaphragm, showed a 7.1 pF zero pressure capacitance, and 5.2 % F.S, sensitivity in 10 KPa pressure range. By using a capacitance to voltage converter, the thermal zero shift of 0.051 %F.S./$^{\circ}C$ and the thermal sensitivity shift of 0.12 %F.S./$^{\circ}C$ for temperature range of $5{\sim}45^{\circ}C$ were obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.541-547
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• 2019

Recent developments in hacking technology are continuing to increase the number of new security vulnerabilities. Approximately 80,000 new vulnerabilities have been registered in the Common Vulnerability Enumeration (CVE) database, which is a representative vulnerability database, from 2010 to 2015, and the trend is gradually increasing in recent years. While security vulnerabilities are growing at a rapid pace, responses to security vulnerabilities are slow to respond because they rely on manual analysis. To solve this problem, there is a need for a technology that can automatically detect and patch security vulnerabilities and respond to security vulnerabilities in advance. In this paper, we propose the technology to extract the features of the vulnerability-discovery target binary through complexity analysis, and select a vulnerability-discovery strategy suitable for the feature and automatically explore the vulnerability. The proposed technology was compared to the AFL, ANGR, and Driller tools, with about 6% improvement in code coverage, about 2.4 times increase in crash count, and about 11% improvement in crash incidence.

• Mass Spectrometry Letters
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• v.13 no.3
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• pp.49-57
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• 2022

During electrospray ionization mass spectrometry (ESI-MS) analysis of proteins, the addition of supercharging agents allows for adjusting the maximal charge state, affecting the charge state distribution, and increases the number of ions reaching the detector thus, improving signal detection. We postulate that in di-substituted arene isomers, molecules with higher polarizability values should generate greater interactions and hence elicit higher signal intensities. Polarizability is an electronic parameter which has been demonstrated to predict many chemical interactions. Many properties can be predicted based on charge polarization. Molecular polarizability is a vital descriptor for explaining intermolecular interactions. We employed DFT (density functional/Hartree-Fock hybrid model, B3LYP)-derived descriptors and computed molecular polarizability for ten disubstituted arene reagents, each set made up of three (ortho, meta, para) isomers, with reported use as supercharging reagents during ESI experiments. The atomic electronic inputs were ionization potential (IP), electron affinity (EA), electronegativity (𝛘), hardness (η), chemical potential (µ), and dipole moment (D). We determined that the para isomers showed the highest polarizability values in nine of the ten sets. There was no difference between the ortho and meta isomers. Polarizability also increased with increasing complexity of the substituents on the benzene ring. Polarizability correlated positively with IP, EA, 𝛘, η, and D but correlated negatively with chemical potential. This DFT study predicts that the para isomers of di-substituted arene isomers should elicit the strongest ESI responses. An experimental comparison of the three isomers, especially of larger supercharging molecules, could be carried out to establish this premise.

• Mycobiology
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• v.49 no.6
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• pp.589-598
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• 2021

White strains of Hypsizygus marmoreus are more difficult to cultivate than are brown strains; therefore, new white strain breeding strategies are required. Accordingly, we constructed the genetic map of H. marmoreus with 1996 SNP markers on 11 linkage groups (LGs) spanning 1380.49 cM. Prior to analysis, 82 backcrossed strains (HM8 lines) were generated by mating between KMCC03106-31 and the progenies of the F1 hybrid (Hami-18 × KMCC03106-93). Using HM8, the first 23 quantitative trait loci (QTLs) of yield-related traits were detected with high limit of detection (LOD) scores (1.98-9.86). The length, thickness, and hardness of the stipe were colocated on LG 1. Especially, length of stipe and thickness of stipe were highly correlated given that the correlation coefficients were negative (-0.39, p value ≤ .01). And a typical biomodal distribution was observed for lightness of the pileus and the lightness of the pileus trait belonged to the LG 8, as did traits of earliness and mycelial growth in potato dextrose agar (PDA) medium. Therefore, results for color traits can be suggested that color is controlled by a multi-gene of one locus. The yield trait was highly negatively correlated with the traits for thickness of the stipe (-0.45, p value ≤ .01). Based on additive effects, the white strain was confirmed as recessive; however, traits of mycelial growth, lightness, and quality were inherited by backcrossed HM8 lines. This new genetic map, finely mapped QTLs, and the strong selection markers could be used in molecular breeding of H. marmoreus.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.14
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• pp.165-172
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• 1973

The sterile phenomenon is frequently found in the inter-species hybrids of ginseng as in other plants. It is known that among the hybrids between Panax Ginseng (PG) and Panax Quinquefolium (PQ), and between Panax Ginseng and Paxax Japonicus (PI), PG${\times}$PI is fertile only very rarely, while PG ${\times}$ PQ is always sterile. Therefore, in order to clarify the relationship between this sterility phenomenon and the metabolism of free amino acids, the changes of free amino acids through the formation of the flower organs and seeds of two hybrids, PG ${\times}$ PQ and PG ${\times}$ PI were investigated by thin layer chromatography. The results are summarized as follows: 1. Distinct differences in the quantity and number of free amino acids were recognized between PG ${\times}$ PQ, PG ${\times}$ PI and their parent plants. From the hybrid PG ${\times}$ PQ, 19 kinds of ninhyrin sensitive substances were detected in all. They were (1) 17 amino acids: alanine, valine, leucine, phenylalanine, proline, hydroxy-proline, serine, threonine, tyrosine, aspartic acid, glutamic acid, lysine, arginine, ${\gamma}$-amino butyric acid, ${\beta}$-alanine, cysteic acid and tryptophan, and (2) two amides: asparagine and glutamine. From the hybrid PG ${\times}$ PI, in addition to the above 19 substances, methionine and one unknown substance were detected. 2. Generally, alanine, as partie acid, glutamic acid, cysteic acid and asparagine were detected in large amounts in the two hybrids as in PG, PG and PJ but it was a noticeable fact concerning these two hybrids that the largest quantity of asparagine was found at microspore satge and pollen mature stage. 3. The decrease of cysteic acid in the two hybrids at the red ripened stage was the same as in PQ and PJ but opposite to the change in PG. The detection of methionine in PG ${\times}$ PJ was worthy of notice. 4. The change of proline was conspicuously different from that in their parent plants. It was detected as a trace of color at the micros pore stage while asparagine was detected in the greatest amount at that time. It is well known that the quantity of proline is closely related to the sterility of plant. This fact was also found true in the formation of ginseng seeds. It was reported as well that asparagine accumulated when proline decreased. 5. The deficiency of proline seemed to be closely related with the sterility of hybrids and with the degradation of pollen in anther. 6. The difference in the changes of free amino acids between the selfed lines of PG, PQ and PJ, and their hybrids seemed to be caused by the transformation of gene-action system by hybridization. On these phenomena along with proline metabolim and its physiological role in seed formation further studies are required.