• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1689-1705
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• 2023

To deal with the potential XSS vulnerabilities in the source code of the power communication network, an XSS vulnerability detection method combining the static analysis method with the dynamic testing method is proposed. The static analysis method aims to analyze the structure and content of the source code. We construct a set of feature expressions to match malignant content and set a "variable conversion" method to analyze the data flow of the code that implements interactive functions. The static analysis method explores the vulnerabilities existing in the source code structure and code content. Dynamic testing aims to simulate network attacks to reflect whether there are vulnerabilities in web pages. We construct many attack vectors and implemented the test in the Selenium tool. Due to the combination of the two analysis methods, XSS vulnerability discovery research could be conducted from two aspects: "white-box testing" and "black-box testing". Tests show that this method can effectively detect XSS vulnerabilities in the source code of the power communication network.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.4
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• pp.345-355
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• 2014

This paper focuses on aerodynamic and inertial modeling of the propeller for its applications in flight dynamics analyses of a propeller-driven airplane. Unsteady aerodynamic and inertial loads generated by the propeller are formulated using the blade element method, where the local velocity and acceleration vectors for each blade element are obtained from exact kinematic relations for general maneuvering conditions. Vortex theory is applied to obtain the flow velocities induced by the propeller wake, which are used in the computation of the aerodynamic forces and moments generated by the propeller and other aerodynamic surfaces. The vortex lattice method is adopted to obtain the induced velocity over the wing and empennage components and the related influence coefficients are computed, taking into account the propeller induced velocities by tracing the wake trajectory trailing from each of the propeller blades. Aerodynamic forces and moments of the fuselage and other aerodynamic surfaces are computed by using the wind tunnel database and applying strip theory to incorporate viscous flow effects. The propeller models proposed in this paper are applied to predict isolated propeller performances under steady flight conditions. Trimmed level forward and turn flights are analyzed to investigate the effects of the propeller on the flight characteristics of a propeller-driven light-sports airplane. Flight test results for a series of maneuvering flights using a scaled model are employed to run the flight dynamic analysis program for the proposed propeller models. The simulations are compared with the flight test results to validate the usefulness of the approach. The resultant good correlations between the two data sets shows the propeller models proposed in this paper can predict flight characteristics with good accuracy.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.250-256
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• 2014

Non-reference P frame coding is used to enhance coding efficiency in low-delay encoding configuration of Internet Video Coding (IVC), which is being standardized as a royalty-free video codec in MPEG. The existing method of non-reference P frame coding which was adopted in the reference Test Model of IVC (ITM) 4.0 adaptively applies a non-reference P frame with a fixed coding structure based on the magnitude of motion vectors (MVs), however, which unexpectedly degrades the coding efficiency for some sequences. In this paper, the existing non-reference P frame coding is improved by changing non-reference P frame coding structure and applying a new adaptive method using the ratio of the amount of generated bits of non-reference frames to that of reference frames as well as MVs. Experimental results show that the proposed non-reference P frame coding gives 6.6% BD-rate bit saving in average over ITM 7.0.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.40-49
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• 1994

In this paper, we propose methods for improving the performance of word recognition system. The ray stratey of the first method is to apply the inertia to the feature vector sequences of speech signal to stabilize the transitions between VQ cdoes. The second method is generating the new observation probabilities using the transition matrix of VQ codes as weights at the observation probability of the output symbol, so as to take into account the time relation between neighboring frames in DHMM. By applying the inertia to the feature vector sequences, we can reduce the overlapping of probability distribution of the response paths for each word and stabilize state transitions in the HMM. By using the transition matrix of VQ codes as weights in conventional DHMM. we can divide the probability distribution of feature vectors more and more, and restrict the feature distribution to a suitable region so that the performance of recognition system can improve. To evaluate the performance of the proposed methods, we carried out experiments for 50 DDD area names. As a result, the proposed methods improved the recognition rate by $4.2\%$ in the speaker-dependent test and $12.45\%$ in the speaker-independent test, respectively, compared with the conventional DHMM.

• Korean journal of applied entomology
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• v.21 no.2 s.51
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• pp.53-60
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• 1982

Isolates of soybean mosaic virus (SMV) strains classified based on virulence in silt resistant soybean cultivars caused the same reactions in soybean cultivars used as differentials as those obtained by sap inoculations to the same cultivars. Five species of aphids (Myzus persicae SULZ., Aphis craccivora KOCH, Aphis citricola VAN., Rhopalosiphum maidis FIT., End R. padi L.) were able to transmit each of SMV strains. However, R. maidis and R. padi were inefficient vectors for transmission of SMV strain G3. Spread if four SMV strains (G2, G3, G6, and G7) was monitored in the field from sapinoculated plants in a one meter row of Williams soybeans (source plants) to plants in an adjacent row of Williams 80cm away (test plants). Test plants wert downwind from the source plants. A complete block design was used. Spread of strain G6 was significantly greater than that of other three strains. Two hundred six aphids were collected from June 27, 1979 to August 2, 1979 in the same field. A. citricola was the mist prevalent, comprising $68\%$ of the total aphids. Yields of Williams inoculated with each strain were also compared. Yields were the least from plants inoculated with strain G2 following G6, G3, and G7 in that order.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.5
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• pp.37-47
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• 2004

The security of personal informations has been an important issue since the field of smart card applications has been expanded explosively. The security of smart card is based on cryptographic algorithms, which are highly required to be implemented into hardware for higher speed and stronger security. In this paper, a SEED cryptographic processor is designed by employing one round key generation block which generates 16 round keys without key registers and one round function block which is used iteratively. Both the round key generation block and the F function are using only one G function block with one 5${\times}$l MUX sequentially instead of 5 G function blocks. The proposed SEED processor has been implemented such that each round operation is divided into seven sub-rounds and each sub-round is executed per clock. Functional simulation of the proposed cryptographic processor has been executed using the test vectors which are offered by Korea Information Security Agency. In addition, we have evaluated the proposed SEED processor by executing VHDL synthesis and FPGA board test. The die area of the proposed SEED processor decreases up to approximately 40% compared with the conventional processor.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.41-49
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• 2022

The average acoustic distribution of American English speakers was statistically compared with the English-speaking patterns of gifted students in a Science Academy in Korea. By analyzing speech recordings, the duration time of which is much longer than in previous studies, this research identified the degree of acoustic proximity between the two parties and the predictability of English academic achievement of gifted high school students. Long-term spectral acoustic power distribution vectors were obtained for 2,048 center frequencies in the range of 20 Hz to 20,000 Hz by applying an long-term average speech spectrum (LTASS) MATLAB code. Three more variables were statistically compared to discover additional indices that can predict future English academic achievement: the receptive vocabulary size test, the cumulative vocabulary scores of English formative assessment, and the English Speaking Proficiency Test scores. Linear regression and correlational analyses between the four variables showed that the receptive vocabulary size test and the low-frequency vocabulary formative assessments which require both lexical and domain-specific science background knowledge are relatively more significant variables than a basic suprasegmental level English fluency in the predictability of gifted students' academic achievement.

• Korean Journal Plant Pathology
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• v.3 no.2
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• pp.108-113
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• 1987

Rice black-streaked dwarf virus(RBSDV) was purified from infected maize leaves. Antiserum against RBSDV was prepared for virus detection by enzyme-linked immunosorbent assay(ELISA). In detection of RBSDV by ELISA, effective dilution range of antiserum extracted in RBSDV-containing host plants and insect vectors was from 320 to 2,560 times in rice plant, 320 to 5,120 in maize plant, and 160 to 2,560 times in insect vector, Laodelphax striatellus F, respectively. The percentage of viruliferous vector in overwintered nymphs of Laodelphax striatellus determined by ELISA were 3.0 in Milyang, 2.3 in Chilgok, and 3.7 in Sunsan area. Dead insect vector which could not be tested for vims infection by conventional rice seedling inoculation test could be tested by ELISA. One hundred plants of rice and maize were randomly sampled in the field and tested whether or not they were infected with RBSDV. In rice plants, 4 out of 98 plants turned out to be infected with RBSDV by ELISA. In maize plant, 3 out of 92 plants which were excepted 8 plants to be appeared symptom already were infected. As a result, ELISA could be detected even in case of symptomless plants at early stage of viral infection.