We describe the construction and immunobiological properties of a novel whooping cough vaccine candidate, in which the aroQ gene, encoding 3-dehydroquinase, was deleted by insertional inactivation using the kanamycin resistance gene cassette and allelic exchange using a Bordetella suicide vector. The aroQ B. pertussis mutant required supplementation of media to grow but failed to grow on an unsupplemented medium. The aroQ B. pertussis mutant was undetectable in the trachea and lungs of mice at days 6 and 12 post-infection, respectively. Antigen-specific antibody isotypes IgG1 and IgG2a, were produced, and cell-mediated immunity [CMI], using interleukin-2 and interferon-gamma as indirect indicators, was induced in mice vaccinated with the aroQ B. pertussis vaccine candidate, which were substantially enhanced upon second exposure to virulent B. pertussis. Interleukin-12 was also produced in the aroQ B. pertussis-vaccinated mice. On the other hand, neither IgG2a nor CMI-indicator cytokines were produced in DTaP-vaccinated mice, although the CMI-indicator cytokines became detectable post-challenge with virulent B. pertussis. Intranasal immunization with one dose of the aroQ B. pertussis mutant protected vaccinated mice against an intranasal challenge infection, with no pathogen being detected in the lungs of immunized mice by day 7 post-challenge. B. pertussis aroQ thus constitutes a safe, non-reverting, metabolite-deficient vaccine candidate that induces both humoral and cell-mediated immune responses with potential for use as a single-dose vaccine in adolescents and adults, in the first instance, with a view to disrupting the transmission cycle of whooping cough to infants and the community.
The paper is basically designed to reveal substitutability or complementary nature of export and import among Korea, China, and Japan by employing unit root test, cointegration technique, and vector error correction model(VECM). Empirical evidences are shown that the trading among these countries has been dominated by a complementary nature in the short run which enables it to promote trading in those countries. In the long run, however, the substitutability nature effects strongly to the trading among Korea, China, and Japan. To this end, it could be tentatively concluded that market-oriented trading policies are more effective to stimulate the export and import in those countries in the short run, while a trading policy has to be selectively implemented by the substitutability nature in the long run basis. For instance, a stability policy for exchange rates and various commercial policies could be set for a short term target. Whereas, the substitutability nature should be counted in building up a new industrial structure or in implementing FTA agreement among Korea, China, and Japan.
KSII Transactions on Internet and Information Systems (TIIS)
/
v.18
no.2
/
pp.456-477
/
2024
With information technology's rapid development, the Internet faces serious security problems. Studies have shown that malware has become a primary means of attacking the Internet. Therefore, adversarial samples have become a vital breakthrough point for studying malware. By studying adversarial samples, we can gain insights into the behavior and characteristics of malware, evaluate the performance of existing detectors in the face of deceptive samples, and help to discover vulnerabilities and improve detection methods for better performance. However, existing adversarial sample generation methods still need help regarding escape effectiveness and mobility. For instance, researchers have attempted to incorporate perturbation methods like Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), and others into adversarial samples to obfuscate detectors. However, these methods are only effective in specific environments and yield limited evasion effectiveness. To solve the above problems, this paper proposes a malware adversarial sample generation method (PixGAN) based on the pixel attention mechanism, which aims to improve adversarial samples' escape effect and mobility. The method transforms malware into grey-scale images and introduces the pixel attention mechanism in the Deep Convolution Generative Adversarial Networks (DCGAN) model to weigh the critical pixels in the grey-scale map, which improves the modeling ability of the generator and discriminator, thus enhancing the escape effect and mobility of the adversarial samples. The escape rate (ASR) is used as an evaluation index of the quality of the adversarial samples. The experimental results show that the adversarial samples generated by PixGAN achieve escape rates of 97%, 94%, 35%, 39%, and 43% on the Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Convolutional Neural Network and Recurrent Neural Network (CNN_RNN), and Convolutional Neural Network and Long Short Term Memory (CNN_LSTM) algorithmic detectors, respectively.
Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.
The use of barley seeder attached to rotary tiller in the rural area has a significant meaning not only for the solution of labor peak season, but also for the increase of land utilization efficiency. The facts that presently being used barley seeders are all based on the mechanical principles of the reverse rotation, center drive and are all using forward rotating tine, which is used to be easily and heavily worn out when it rotates reversely, raise problem of recommending them to rural area in Korea. Therefore, the main objective of the study was to develop new type of rotary tine attachable to barley seeders. To attain the objective the following approaches were applied. (1) The kinematic analysis of reverse rotating barley seeders. (2) The studies on the soil bin and artificial soil. (3) The comparative experiment on the power requirement of prototype tine. The results obtained from the studies are summarized as follow: 1. The kinematic analysis of barley seeder attached to rotary tiller: The following results were obtained from the kinematic analysis for deriving general formulae of the motion and velocity characterizing the rotary tine of barley seeders presently being used by farmers. a) The position vector (P) of edge point (P) in the rotary tine of reverse rotating, center drive was obtained by the following formula. $$P=(vt+Rcos wt)i+Rsin wt j+ \{ Rcos \theta r sin \alpha cos (wt- \beta +\theta r) +Rsin \theta r sin \alpha sin (wt-\beta + \theta r) \} lk $$ b) The velocity of edge point $(P^')$ of reverse rotating, center drive rotary tine was obtained by the following formula. $$(P^')=(V-wR sin wt)i+(w\cdot Rcoswt)j + \{ -w\cdot Rcos \theta r\cdot sin \alpha \cdot sin (wt-\beta +\theta r) + w\cdot Rsin \theta r\cdot sin \alpha \cdot cos (wt- \beta + \theta r \} k $$ c) In order to reduce the power requirement of rotary tine, the angle between holder and edge point was desired to be reduced. d) In order to reduce the power requirement, the edge point of rotary tine should be moved from the angle at the begining of cutting to center line of machine, and the additional cutting width should be also reduced. 2. The studies on the soil bin and artificial soil: In order to measure the power requirement of various cutting tines under the same physical condition of soil, the indoor experiments Viere conducted by filling soil bin with artificially made soil similar to the common paddy soil and the results were as follows: a) When the rolling frequencies$(x)$ of the artificial soil were increased, the densIty$(Y)$ was also increased as follows: $$y=1.073200 +0.070780x - 0.002263x^2 (g/cm^3)$$ b) The absolute hardness $(Y)$ of soil had following relationship with the rolling frequencies$(x)$ and were increased as the rolling frequencies were increased. $$Y=37.74 - \frac {0.64 + 0.17x-0. 0054x^2} {(3.36-0.17x + 0.0054x^2)^3} (kg/cm^3)$$ c) The density of soil had significant effect on the cohesion and angle of internal friction of soil. For instance, the soil with density of 1.6 to 1.75 had equivalent density of sandy loam soil with 29.5% of natural soil moisture content. d) The coefficient of kinetiic friction of iron plate on artificial soil was 0.31 to 0.41 and was comparable with that of the natural soil. e) When the pulling speed of soil bin was the 2nd forward speed of power tiller, the rpm of driving shaft of rotary was similar to that of power tiller, soil bin apparatus is indicating the good indoor tester. 3. The comparative experiment on the power requirement of prototype tine of reverse rotating rotary: According to the preliminary test of rotary tine developed with various degrees of angle between holder and edge pcint due to the kinematic analysis, comparative test between prototype rotary tine with $30 ^\circ $ and $10 ^\circ$ of it and presently being used rotary tine was carried out 2nd the results were as follows: a) The total cutting torque was low when the angle between holder and edge point was reduced. b) $\theta r$ (angle between holder and edge point) of rotary tine seemed to be one: of the factors maximizing the increase of torque. c) As the angle between holder and edge point ($\theta r$) of rotary tine was $30 ^\circ $ rather than $45 ^\circ $, the angle of rotation during cutting soil was reduced and the total cutting torque was accordingly reduced about 10%, and the reduction efficiency of total cutting torque was low when the angle between holder and edge point ($\theta r$) of rotary tine was $10 ^\circ $, which indicates that the proper angle between holder and edge point of rotary tine should be larger than $10 ^\circ $ and smaller than $30 ^\circ $ . From above results, it could be concluded that the use of the prototype rotary tine which reduced the angle between holder and edge point to $30 ^\circ $, insted of $45 ^\circ $, is disirable not only decreasing the power requirements, but also increasing the durabie hour of it. Also forward researches are needed, WIlich determine the optimum tilted angle of rotary brocket, and rearrangement of the rotary tine on the rotary boss.
Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.
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